S. Schweber and M. Wachter, Complex Systems, Modelling and Simulation, Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, vol.31, issue.4, pp.583-609, 2000.
DOI : 10.1016/S1355-2198(00)00030-7

M. Heymann, Understanding and misunderstanding computer simulation: The case of atmospheric and climate science???An introduction, Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, vol.41, issue.3, pp.193-200, 2010.
DOI : 10.1016/j.shpsb.2010.08.001

M. Sundberg, Cultures of simulations vs. cultures of calculations? The development of simulation practices in meteorology and astrophysics, Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, vol.41, issue.3, pp.273-281, 2010.
DOI : 10.1016/j.shpsb.2010.07.004

O. H. Pilkey and L. Pilkey-jarvis, Useless Arithmetic: Why Environmental Scientists Can't Predict the Future, 2007.

J. C. Helton and C. J. Sallaberry, Conceptual basis for the definition and calculation of expected dose in performance assessments for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada, Reliability Engineering & System Safety, vol.94, issue.3, pp.677-698, 2009.
DOI : 10.1016/j.ress.2008.06.011

J. C. Helton, C. W. Hansen, and C. J. Sallaberry, Uncertainty and sensitivity analysis in performance assessment for the proposed repository for high-level radioactive waste at Yucca Mountain, Nevada. Reliab. Eng. Syst. Safe. in press, 2011.

Y. Zheng, W. Wang, F. Han, and J. Ping, Uncertainty assessment for watershed water quality modeling: A Probabilistic Collocation Method based approach, Advances in Water Resources, vol.34, issue.7, pp.887-898, 2011.
DOI : 10.1016/j.advwatres.2011.04.016

N. Eckert, M. Naaim, and E. Parent, Long-term avalanche hazard assessment with a Bayesian depth-averaged propagation model, Journal of Glaciology, vol.56, issue.198, pp.563-586, 2010.
DOI : 10.3189/002214310793146331

O. Asserin, A. Loredo, M. Petelet, and B. Iooss, Global sensitivity analysis in welding simulations -What are the material data you really need? Fin, El. Analys. Des, vol.47, pp.1004-1016, 2011.

C. J. Hopfe and J. L. Hensen, Uncertainty analysis in building performance simulation for design support, Energy and Buildings, vol.43, issue.10, pp.2798-2805, 2011.
DOI : 10.1016/j.enbuild.2011.06.034

I. Vernon, M. Goldstein, and R. G. Bower, Galaxy formation: a Bayesian uncertainty analysis, Bayesian Analysis, vol.5, issue.4, pp.619-670, 2010.
DOI : 10.1214/10-BA524

M. Crucifix and J. Rougier, On the use of simple dynamical systems for climate predictions, The European Physical Journal Special Topics, vol.174, issue.1, pp.11-31, 2009.
DOI : 10.1140/epjst/e2009-01087-5

A. Antoniadis, C. Helbert, C. Prieur, and L. Viry, Spatio-temporal prediction for West African monsoon, Environmetrics in press, 2011.
DOI : 10.1002/env.1134

URL : https://hal.archives-ouvertes.fr/hal-00551303/file/prieur.pdf

A. Allard, N. Fischer, F. Didieux, E. Guillaume, and B. Iooss, Evaluation of the most influent input variables on quantities of interest in a fire simulation, J. Soc. Franc. Stat, vol.152, pp.103-117, 2011.

P. Baraldi, N. Pedroni, E. Zio, E. Ferrario, A. Pasanisi et al., Monte Carlo and fuzzy interval propagation of hybrid uncertainties on a risk model for the design of a flood protection dike, Advances in Safety, Reliability and Risk Management: ESREL 2011, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00658077

O. Hagan, A. Buck, C. E. Daneshkhah, A. Eiser, J. R. Garthwaite et al., Uncertain judgements: eliciting expert probabilities, 2006.

C. Shannon, A Mathematical Theory of Communication, Bell System Technical Journal, vol.27, issue.3, pp.379-423, 1948.
DOI : 10.1002/j.1538-7305.1948.tb01338.x

P. Embrechts, F. Lindskog, and A. Mcneil, Modelling Dependence with Copulas and Applications to Risk Management, Handbook of Heavy Tailed Distributions in Finance, pp.329-384, 2003.
DOI : 10.1016/B978-044450896-6.50010-8

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.23.5130

A. Dutfoy and R. Lebrun, A practical approach to dependence modeling using copulas, Proc. Inst, pp.347-361, 2009.
DOI : 10.1243/1748006xjrr226

R. Lebrun and A. Dutfoy, An innovating analysis of the Nataf transformation from the copula viewpoint, Probabilistic Engineering Mechanics, vol.24, issue.3, pp.312-320, 2009.
DOI : 10.1016/j.probengmech.2008.08.001

D. Moral and P. , Feynman-Kac Formulae -Genealogical and interacting particle systems with applications, 2004.

R. Lebrun and A. Dutfoy, A generalization of the Nataf transformation to distributions with elliptical copula, Probabilistic Engineering Mechanics, vol.24, issue.2, pp.172-178, 2009.
DOI : 10.1016/j.probengmech.2008.05.001

R. Lebrun and A. Dutfoy, Do Rosenblatt and Nataf isoprobabilistic transformations really differ?, Probabilistic Engineering Mechanics, vol.24, issue.4, pp.577-584, 2009.
DOI : 10.1016/j.probengmech.2009.04.006

M. Rosenblatt, Remarks on a Multivariate Transformation, The Annals of Mathematical Statistics, vol.23, issue.3, pp.470-472, 1952.
DOI : 10.1214/aoms/1177729394

K. Dolinski, First-order second-moment approximation in reliability of structural systems: Critical review and alternative approach, Structural Safety, vol.1, issue.3, pp.211-231, 1983.
DOI : 10.1016/0167-4730(82)90027-3

A. M. Hasofer and N. C. Lind, Exact and invariant second moment code format, J. Eng. Mech, vol.100, pp.111-121, 1974.

L. Tvedt, Second order probability by an exact integral, 2nd IFIP Working Conference on Reliability and Optimization on Structural Systems, pp.377-384, 1988.
DOI : 10.1007/978-3-642-83828-6_26

R. G. Ghanem and P. D. Spanos, Stochastic Finite Elements: A Spectral Approach, 2003.
DOI : 10.1007/978-1-4612-3094-6

J. Sacks, W. J. Welch, T. J. Mitchell, and H. P. Wynn, Design and Analysis of Computer Experiments, Statistical Science, vol.4, issue.4, pp.409-435, 1989.
DOI : 10.1214/ss/1177012413

A. Saltelli, S. Tarantola, F. Campolongo, and M. Ratto, Sensitivity analysis in practice: a guide to assessing scientific models, 2004.
DOI : 10.1002/0470870958

T. Open, Open Treatment of Uncertainties, Risk's aNd Statistics, an open source source platform

M. Saito and M. Matsumoto, SIMD-Oriented Fast Mersenne Twister: a 128-bit Pseudorandom Number Generator
DOI : 10.1007/978-3-540-74496-2_36

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.98.4500

J. A. Doornik, An Improved Ziggurat Method to Generate Normal Random Samples . Working paper, 2005.

G. Marsaglia and W. W. Tsang, The Ziggurat Method for Generating Random Variables, Journal of Statistical Software, vol.5, issue.8, pp.1-7, 2000.
DOI : 10.18637/jss.v005.i08

URL : http://doi.org/10.18637/jss.v005.i08

D. Benton and K. Krishnamoorthy, Computing discrete mixtures of continuous distributions: noncentral chisquare, noncentral t and the distribution of the square of the sample multiple correlation coefficient, Computational Statistics & Data Analysis, vol.43, issue.2, pp.249-267, 2003.
DOI : 10.1016/S0167-9473(02)00283-9

G. Blatman and B. Sudret, 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

M. Zuniga, M. Garnier, J. Remy, E. De-rocquigny, and E. , Analysis of adaptive directional stratification for the controlled estimation of rare event probabilities, Stat. Comput. in press, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00708150

A. Arnaud, N. Goutal, and E. De-rocquigny, Influence des incertitudes sur les hydrogrammes de vidange de retenue en cas de rupture progressive dun barrage en enrochements sur les zones inondées en aval, SimHydro 2010 Conference, 2010.

N. Goutal and F. Maurel, A finite volume solver for 1D shallow-water equations applied to an actual river, International Journal for Numerical Methods in Fluids, vol.148, issue.1, pp.1-19, 2002.
DOI : 10.1002/fld.201

M. Berveiller and G. Blatman, Sensitivity and reliability analysis of a globe valve using an adaptive sparse polynomial chaos expansion, 11th International Conference on Applications of Statistics and Probability in Civil Engineering, 2011.
DOI : 10.1201/b11332-98

E. R&d, Code Aster, Analysis of Structures and Thermomechanics for Studies & Research

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

T. Crestaux, J. M. Martinez, and O. Le-maitre, Polynomial chaos expansion for sensitivity analysis, Reliability Engineering & System Safety, vol.94, issue.7, pp.1161-1172, 2009.
DOI : 10.1016/j.ress.2008.10.008

O. Hagan and A. , Bayesian analysis of computer code outputs: a tutorial, Reliab. Eng. Syst. Safe, vol.91, pp.1290-1300, 2006.

M. Goldstein, J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid et al., External Bayesian Analysis for Computer Simulators*, Bayesian Statistics 9, pp.201-228, 2011.
DOI : 10.1093/acprof:oso/9780199694587.003.0007

G. Celeux, A. Grimaud, Y. Lefebvre, and E. De-rocquigny, Identifying intrinsic variability in multivariate systems through linearised inverse methods, INRIA Research Report RR, p.6400, 2007.
DOI : 10.1080/17415971003624330

URL : https://hal.archives-ouvertes.fr/inria-00200113

T. Aven, Some reflections on uncertainty analysis and management, Reliability Engineering & System Safety, vol.95, issue.3, pp.195-201, 2010.
DOI : 10.1016/j.ress.2009.09.010

P. Limbourg and E. De-rocquigny, Uncertainty analysis using evidence theory ??? confronting level-1 and level-2 approaches with data availability and computational constraints, Reliability Engineering & System Safety, vol.95, issue.5, pp.550-564, 2010.
DOI : 10.1016/j.ress.2010.01.005

L. Duy, T. D. Vasseur, D. Couplet, M. Dieulle, L. Bérenguer et al., A study on updating belief functions for parameter uncertainty representation in Nuclear Probabilistic Risk Assessment, 7th International Symposium on Imprecise Probability: Theories and Applications, 2011.

P. Baraldi, N. Pedroni, E. Zio, E. Ferrario, A. Pasanisi et al., Monte Carlo and fuzzy interval propagation of hybrid uncertainties on a risk model for the design of a flood protection dike, Advances in Safety, Reliability and Risk Management: ESREL 2011, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00658077

F. Campolongo, S. Tarantola, and A. Saltelli, Tackling quantitatively large dimensionality problems, Computer Physics Communications, vol.117, issue.1-2, pp.75-85, 1999.
DOI : 10.1016/S0010-4655(98)00165-9

. Morris, Factorial Sampling Plans for Preliminary Computational Experiments, Technometrics, vol.1, issue.2, pp.161-174, 1991.
DOI : 10.2307/1266468

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.584.521

D. Rocquigny, E. Devictor, N. Tarantola, and S. , Uncertainty in Industrial Practice, 2008.
DOI : 10.1002/9780470770733

D. Kurowicka and R. Cooke, Uncertainty analysis with high dimensional dependence modelling, 2006.
DOI : 10.1002/0470863072

C. Xu and G. Z. Gertner, Uncertainty and sensitivity analysis for models with correlated parameters, Reliability Engineering & System Safety, vol.93, issue.10, pp.1563-1573, 2008.
DOI : 10.1016/j.ress.2007.06.003

G. Li, H. Rabitz, P. E. Yelvington, O. O. Oluwole, F. Bacon et al., Global Sensitivity Analysis for Systems with Independent and/or Correlated Inputs, The Journal of Physical Chemistry A, vol.114, issue.19, pp.6022-6032, 2010.
DOI : 10.1021/jp9096919

E. Borgonovo, 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

S. Kucherenko, M. Munoz-zuniga, S. Tarantola, and . Annoni, Metamodelling and Global Sensitivity Analysis of Models with Dependent Variables, AIP Conf. Proc. 1389, pp.1913-1916, 2011.
DOI : 10.1063/1.3636986