Sensitivity analysis of complex models: Coping with dynamic and static inputs, Reliability Engineering & System Safety, vol.134, pp.268-275, 2015. ,
DOI : 10.1016/j.ress.2014.08.010
URL : https://hal.archives-ouvertes.fr/hal-01063795
Some basic hypergeometric orthogonal polynomials that generalize Jacobi polynomials, Memoirs of the American Mathematical Society, vol.54, issue.319, p.55, 1985. ,
DOI : 10.1090/memo/0319
Efficient computation of global sensitivity indices using sparse polynomial chaos expansions, Reliability Engineering & System Safety, vol.95, issue.11, pp.1216-1229, 2010. ,
DOI : 10.1016/j.ress.2010.06.015
Adaptive sparse polynomial chaos expansion based on least angle regression, Journal of Computational Physics, vol.230, issue.6, pp.2345-2367, 2011. ,
DOI : 10.1016/j.jcp.2010.12.021
Measuring Uncertainty Importance: Investigation and Comparison of Alternative Approaches, Risk Analysis, vol.2, issue.1, pp.1349-1361, 2006. ,
DOI : 10.1016/S0951-8320(02)00229-6
A new uncertainty importance measure, Reliability Engineering & System Safety, vol.92, issue.6, pp.771-784, 2007. ,
DOI : 10.1016/j.ress.2006.04.015
A Common Rationale for Global Sensitivity Measures and Their Estimation, Risk Analysis, vol.31, issue.3, pp.1-25, 2016. ,
DOI : 10.1111/risa.12555
Sensitivity analysis: A review of recent advances, European Journal of Operational Research, vol.248, issue.3, pp.1-19, 2015. ,
DOI : 10.1016/j.ejor.2015.06.032
Sensitivity theory for nonlinear systems. I. Nonlinear functional analysis approach, Journal of Mathematical Physics, vol.22, issue.12, pp.2794-2802, 1981. ,
DOI : 10.1063/1.525186
An uncertainty importance measure using a distance metric for the change in a cumulative distribution function, Reliability Engineering & System Safety, vol.70, issue.3, pp.313-321, 2000. ,
DOI : 10.1016/S0951-8320(00)00068-5
Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory, The Journal of Chemical Physics, vol.59, issue.8, pp.3873-3878, 1973. ,
DOI : 10.1063/1.1680571
On the primary variable switching technique for simulating unsaturated???saturated flows, Advances in Water Resources, vol.23, issue.3, pp.271-301, 1999. ,
DOI : 10.1016/S0309-1708(98)00057-8
Reactive Transport Parameter Estimation and Global Sensitivity Analysis Using Sparse Polynomial Chaos Expansion, Water, Air, & Soil Pollution, vol.30, issue.7, pp.4183-4197, 2012. ,
DOI : 10.1007/s11270-012-1183-8
URL : https://hal.archives-ouvertes.fr/hal-00918155
Sensitivity analysis based on cramer von mises distance, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01163393
On Generating Orthogonal Polynomials, SIAM Journal on Scientific and Statistical Computing, vol.3, issue.3, pp.289-317, 1982. ,
DOI : 10.1137/0903018
Is the recurrence relation for orthogonal polynomials always stable? BIT 33, pp.277-284, 1993. ,
On automatic differentiation In: Mathematical programming: recent developments and applications, pp.83-108, 1989. ,
Adaptive multi-scale parameterization for one-dimensional flow in unsaturated porous media, Advances in Water Resources, vol.31, issue.1, pp.28-43, 2008. ,
DOI : 10.1016/j.advwatres.2007.06.009
URL : https://hal.archives-ouvertes.fr/hal-00321656
Importance measures in global sensitivity analysis of nonlinear models, Reliability Engineering & System Safety, vol.52, issue.1, pp.1-17, 1996. ,
DOI : 10.1016/0951-8320(96)00002-6
Revue sur l'analyse de sensibilité globale de modèles numériques, J. Société Française de Statistique, vol.152, issue.1, pp.3-25, 2011. ,
Estimation of global sensitivity indices for models with dependent variables, Computer Physics Communications, vol.183, issue.4, pp.937-946, 2012. ,
DOI : 10.1016/j.cpc.2011.12.020
Derivative-based global sensitivity measures: General links with Sobol??? indices and numerical tests, Mathematics and Computers in Simulation, vol.87, pp.45-54, 2013. ,
DOI : 10.1016/j.matcom.2013.02.002
URL : https://hal.archives-ouvertes.fr/hal-00666473
Sample-based estimation of correlation ratio with polynomial approximation, ACM Transactions on Modeling and Computer Simulation, vol.18, issue.1, pp.1-16, 2007. ,
DOI : 10.1145/1315575.1315578
Comparison of some efficient methods to evaluate the main effect of computer model factors, Journal of Statistical Computation and Simulation, vol.1, issue.2, pp.167-178, 2008. ,
DOI : 10.1016/S0378-7788(00)00127-4
URL : https://hal.archives-ouvertes.fr/hal-01093033
Variance-based sensitivity indices for models with dependent inputs, Reliability Engineering & System Safety, vol.107, pp.115-121, 2012. ,
DOI : 10.1016/j.ress.2011.08.008
URL : https://hal.archives-ouvertes.fr/hal-01093038
Non-parametric methods for global sensitivity analysis of model output with dependent inputs, Environmental Modelling & Software, vol.72, pp.173-183, 2015. ,
DOI : 10.1016/j.envsoft.2015.07.010
URL : https://hal.archives-ouvertes.fr/hal-01182302
UQLab: A Framework for Uncertainty Quantification in Matlab, Vulnerability, Uncertainty, and Risk, pp.2554-2563, 2014. ,
DOI : 10.1061/9780784413609.257
Nonparametric variance-based methods of assessing uncertainty importance, Reliability Engineering & System Safety, vol.57, issue.3, 1996. ,
DOI : 10.1016/S0951-8320(97)00039-2
A new model for predicting the hydraulic conductivity of unsaturated porous media, Water Resources Research, vol.12, issue.4, pp.513-522, 1976. ,
DOI : 10.1029/WR012i003p00513
Practical and theoretical aspects of adjoint parameter estimation and identifiability in meteorology and oceanography, Dynamics of Atmospheres and Oceans, vol.27, issue.1-4, pp.55-79, 1997. ,
DOI : 10.1016/S0377-0265(97)00032-8
Comparison of sensitivity analysis methods for pollutant degradation modelling: A case study from drinking water treatment, Science of The Total Environment, vol.433, pp.530-537, 2012. ,
DOI : 10.1016/j.scitotenv.2012.06.026
An introduction to sensitivity assessment of simulation models. Environmental Modelling and Software 69, pp.166-174, 2015. ,
Probabilistic sensitivity analysis of complex models: a Bayesian approach, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.34, issue.3, pp.751-769, 2004. ,
DOI : 10.1214/ss/1009213004
Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion, Reliability Engineering & System Safety, vol.106, pp.179-190, 2012. ,
DOI : 10.1016/j.ress.2012.05.002
On Estimation of a Probability Density Function and Mode, The Annals of Mathematical Statistics, vol.33, issue.3, pp.1065-1076, 1962. ,
DOI : 10.1214/aoms/1177704472
On the general theory of skew correlation and non-linear regression, In: Mathematical contributions to the theory of evolution, 1905. ,
An effective algorithm for computing global sensitivity indices (EASI). Reliability Engineering and System Safety 95, pp.354-360, 2010. ,
Global sensitivity measures from given data, European Journal of Operational Research, vol.226, issue.3, pp.536-550, 2013. ,
DOI : 10.1016/j.ejor.2012.11.047
Numerical Recipes: The Art of Scientific Computing, 2007. ,
Efficient input???output model representations, Computer Physics Communications, vol.117, issue.1-2, pp.11-20, 1999. ,
DOI : 10.1016/S0010-4655(98)00152-0
State Dependent Parameter metamodelling and sensitivity analysis, Computer Physics Communications, vol.177, issue.11, pp.863-876, 2007. ,
DOI : 10.1016/j.cpc.2007.07.011
Sensitivity analysis practices: Strategies for model-based inference, Reliability Engineering & System Safety, vol.91, issue.10-11, pp.1109-1125, 2006. ,
DOI : 10.1016/j.ress.2005.11.014
Update 1 of: Sensitivity Analysis for Chemical Models, Chemical Reviews, vol.112, issue.5, pp.1-21, 2012. ,
DOI : 10.1021/cr200301u
On the Relative Importance of Input Factors in Mathematical Models, Journal of the American Statistical Association, vol.97, issue.459, pp.702-709, 2002. ,
DOI : 10.1198/016214502388618447
Sensitivity analysis in practice. Probability and Statistics, 2004. ,
A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output, Technometrics, vol.60, issue.1, pp.39-56, 1999. ,
DOI : 10.1007/BF01166355
Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. II Applications, The Journal of Chemical Physics, vol.59, issue.8, pp.3879-3888, 1973. ,
DOI : 10.1063/1.1680572
Bayesian sparse polynomial chaos expansion for global sensitivity analysis, Computer Methods in Applied Mechanics and Engineering, vol.318, 2016. ,
DOI : 10.1016/j.cma.2017.01.033
URL : https://hal.archives-ouvertes.fr/hal-01476649
Sensitivity estimates for nonlinear mathematical models, Math. Mod. and Comput. Exp, vol.1, pp.407-414, 1993. ,
Derivative based global sensitivity measures and their link with global sensitivity indices, Mathematics and Computers in Simulation, vol.79, issue.10, pp.3009-3017, 2009. ,
DOI : 10.1016/j.matcom.2009.01.023
A new derivative based importance criterion for groups of variables and its link with the global sensitivity indices, Computer Physics Communications, vol.181, issue.7, pp.1212-1217, 2010. ,
DOI : 10.1016/j.cpc.2010.03.006
Quasi-random sequence generator (routine LPTAU51), 1992. ,
An Efficient Method for Computing Single-Parameter Partial Expected Value of PerfectInformation, Medical Decision Making, vol.33, issue.6, pp.755-766, 2013. ,
DOI : 10.1177/0272989X12465123
Global sensitivity analysis using polynomial chaos expansions, Reliability Engineering & System Safety, vol.93, issue.7, pp.964-979, 2008. ,
DOI : 10.1016/j.ress.2007.04.002
URL : https://hal.archives-ouvertes.fr/hal-01432217
Random balance designs for the estimation of first order global sensitivity indices, Reliability Engineering & System Safety, vol.91, issue.6, pp.717-727, 2006. ,
DOI : 10.1016/j.ress.2005.06.003
URL : https://hal.archives-ouvertes.fr/hal-01065897
A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils1, Soil Science Society of America Journal, vol.44, issue.5, pp.892-898, 1980. ,
DOI : 10.2136/sssaj1980.03615995004400050002x
The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations, SIAM Journal on Scientific Computing, vol.24, issue.2, pp.619-644, 2002. ,
DOI : 10.1137/S1064827501387826