X. Ma and N. Zabaras, An adaptive high-dimensional stochastic model representation technique for the solution of stochastic partial differential equations, Journal of Computational Physics, vol.229, issue.10, pp.3884-3915, 2010.
DOI : 10.1016/j.jcp.2010.01.033

Z. Gao and J. Hesthaven, On ANOVA expansions and strategies for choosing the anchor point, Applied Mathematics and Computation, vol.217, issue.7, pp.3274-3285, 2010.
DOI : 10.1016/j.amc.2010.08.061

Z. Zhang, M. Choi, and G. Karniadakis, Anchor Points Matter in ANOVA Decomposition, Lecture Notes in Computational Science and Engineering, vol.76, pp.347-355978, 2011.
DOI : 10.1007/978-3-642-15337-2_32

X. Yang, M. Choi, G. Lin, and G. Karniadakis, Adaptive ANOVA decomposition of stochastic incompressible and compressible flows, Journal of Computational Physics, vol.231, issue.4, pp.1587-1614, 2012.
DOI : 10.1016/j.jcp.2011.10.028

X. Wang, On the approximation error in high dimensional model representation, 2008 Winter Simulation Conference, pp.453-462, 2008.
DOI : 10.1109/WSC.2008.4736100

. Sobol-'i, Theorems and examples on high dimensional model representation, Reliability Engineering & System Safety, vol.79, issue.2, pp.187-193, 2003.
DOI : 10.1016/S0951-8320(02)00229-6

G. Archer, A. Saltelli, and . Sobol-'im, Sensitivity measures,anova-like Techniques and the use of bootstrap, Journal of Statistical Computation and Simulation, vol.2, issue.2, pp.99-120, 1997.
DOI : 10.1142/S0129183195000204

. Sobol-'im, On sensitivity estimation for nonlinear mathematical models, Matem. Mod, vol.2, issue.1, pp.112-118, 1990.

. Sobol-'im, Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates, Mathematics and Computers in Simulation, vol.55, issue.1-3, pp.271-280, 2001.
DOI : 10.1016/S0378-4754(00)00270-6

Z. Zhang, M. Choi, and G. Karniadakis, Error Estimates for the ANOVA Method with Polynomial Chaos Interpolation: Tensor Product Functions, SIAM Journal on Scientific Computing, vol.34, issue.2, pp.1165-1186, 2012.
DOI : 10.1137/100788859

H. Xu and S. Rahman, A generalized dimension-reduction method for multidimensional integration in stochastic mechanics, International Journal for Numerical Methods in Engineering, vol.23, issue.12, pp.1992-2019, 2004.
DOI : 10.1002/nme.1135

G. Li, H. Rabitz, P. Yelvington, O. Oluwole, F. Bacon et al., Global sensitivity analysis for systems with independent and/or correlated inputs. The journal of physical chemistry, pp.6022-6054, 2010.

R. Abgrall, P. Congedo, G. Geraci, and G. Iaccarino, Decomposition and Computation of highorder statistics, INRIA Research Report, p.8193, 2012.

L. Maître, O. Knio, and O. , Spectral Methods for Uncertainty Quantification, 2010.

T. Ishigami and T. Homma, An importance quantification technique in uncertainty analysis for computer models. ISUMA'90, First International Symposium on Uncertainty Modeling and Analysis, pp.398-403, 1990.

B. Sudret, 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

G. Bellas-chatzigeorgis, N. Villedieu, M. Panesi, P. Congedo, and T. Magin, Propagation of uncertainties related to a complex detailed chemical mechanism, UQ4AERO: Uncertainty Quantification for Aerospace Applications, pp.1-90, 2013.

E. Borgonovo, A new uncertainty importance measure Reliability Engineering & System Safety, pp.771-784, 2007.