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All issues Volume 23 (2019) ESAIM: PS, 23 (2019) 387-408 References
Open Access
Issue
ESAIM: PS
Volume 23, 2019
Page(s) 387 - 408
DOI https://doi.org/10.1051/ps/2018001
Published online 28 June 2019
  1. R.J. Beckman and M.D. McKay, Monte Carlo estimation under different distributions using the same simulation. Technometrics 29 (1987) 153–160. [Google Scholar]
  2. E. Borgonovo, Measuring uncertainty importance: investigation and comparison of alternative approaches. Risk Anal. 26 (2006) 1349–1361. [CrossRef] [PubMed] [Google Scholar]
  3. E. Borgonovo, A new uncertainty importance measure. Reliab. Eng. Syst. Saf. 92 (2007) 771–784. [CrossRef] [Google Scholar]
  4. E. Borgonovo and L. Peccati, On the Quantification and Decomposition of Uncertainty, Vol. 41. Springer (2007). [Google Scholar]
  5. M. Brigo and F. Mercurio, Interest Rate Models – Theory and Practice. Springer (2006). [Google Scholar]
  6. G.T. Buzzard and D. Xiu, Variance-based global sensitivity analysis via sparse-grid interpolation and cubature. Commun. Comput. Phys. 9 (2011) 542–567. [Google Scholar]
  7. P. Carr and D. Madan, Option valuation using the fast Fourier transform. J. Comput. Finance 2 (1999) 61–73. [CrossRef] [Google Scholar]
  8. M. Denuit, J. Dhaene, M. Goovaerts and R. Kaas, Actuarial Theory for Dependent Risks: Measures, Orders and Models. Wiley (2005). [CrossRef] [Google Scholar]
  9. E. Fagiuoli, F. Pellerey and M. Shaked, A characterization of the dilation order and its applications. Stat. Pap. 40 (1999) 393–406. [CrossRef] [Google Scholar]
  10. S.L. Heston, A closed-form solution for options with stochastic volatility with applications to bond and currency options. Rev. Financ. Stud. 6 (1993) 327–343. [Google Scholar]
  11. B. Iooss, F. Van Dorpe and N. Devictor, Response surfaces and sensitivity analyses for an environmental model of dose calculations. Reliab. Eng. Syst. Saf. 91 (2006) 1241–1251. [CrossRef] [Google Scholar]
  12. A. Janon, Analyse de sensibilité et réduction de dimension. Application à l’océanographie. Ph.D. thesis, Université de Grenoble (2012). [Google Scholar]
  13. S. Kochar, X. Li and M. Shaked, The total time on test transform and the excess wealth stochastic orders of distributions. Adv. Appl. Probab. 34 (2002) 826–845. [Google Scholar]
  14. F.Y. Kuo, I.H. Sloan, G.W. Wasilkowski and H. Wozniakowski, On decompositions of multivariate functions. Math. Comput. 79 (2010) 953–966. [Google Scholar]
  15. P. Lemaître, E. Sergienko, A. Arnaud, N. Bousquet, F. Gamboa and B. Iooss, Density modification-based reliability sensitivity analysis. J. Stat. Comput. Simul. 85 (2015) 1200–1223. [Google Scholar]
  16. T.A. Mara and S. Tarantola, Variance-based sensitivity indices for models with dependent inputs. Reliab. Eng. Syst. Saf. 107 (2012) 115–121. [CrossRef] [Google Scholar]
  17. A. Müller and D. Stoyan, Comparison Methods for Stochastic Models and Risks. Wiley (2002). [Google Scholar]
  18. A.B. Owen, Sobol’indices and shapley value. SIAM/ASA J. Uncertain. Quantif. 2 (2014) 245–251. [Google Scholar]
  19. F. Pappenberger, K. Beven, M. Ratto and P. Matgen, Multi-method global sensitivity analysis of flood inundation models. Adv. Water Resour. 31 (2008) 1–14. [Google Scholar]
  20. M. Rodriguez-Fernandez, J.R. Banga and F.J. Doyle, Novel global sensitivity analysis methodology accounting for the crucial role of the distribution of input parameters: application to systems biology models. Int. J. Robust Nonlinear Control 22 (2012) 1082–1102. [CrossRef] [Google Scholar]
  21. A. Saltelli, M. Ratto, T. Andres, F. Campolongo, J. Cariboni, D. Gatelli, M. Saisana and S. Tarantola, Global Sensitivity Analysis: The Primer. Wiley (2008). [Google Scholar]
  22. M. Shaked and J.G. Shanthikumar, Two variability orders. Probab. Eng. Inf. Sci. 12 (1998) 1–23. [Google Scholar]
  23. M. Shaked and J.G. Shanthikumar, Stochastic Orders. Springer (2007). [CrossRef] [Google Scholar]
  24. M. Shaked, M.A. Sordo and A. Suarez-Llorens, A class of location-independent variability orders, with applications. J. Appl. Probab. 47 (2010) 407–425. [Google Scholar]
  25. I.M. Sobol, Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Math. Comput. Simul. 55 (2001) 271–280. [Google Scholar]
  26. A.W. van der Vaart, Asymptotic Statistics. Vol. 3 of Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge University Press, Cambridge (1998). [Google Scholar]
  27. H. Varella, M. Guérif and S. Buis, Global sensitivity analysis measures the quality of parameter estimation: the case of soil parameters and a crop model. Environ. Model. Softw. 25 (2010) 310–319. [Google Scholar]
  28. E. Volkova, B. Iooss and F. Van Dorpe, Global sensitivity analysis for a numerical model of radionuclide migration from the RRC “Kurchatov Institute” radwaste disposal site. Stoch. Environ. Res. Risk Assess. 22 (2008) 17–31. [Google Scholar]

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