M. J. Bayarri, J. O. Berger, J. Cafeo, G. Garcia-donato, F. Liu et al., Computer model validation with functional output. The Annals of Statistics, pp.1874-1906, 2007.

J. Bect, D. Ginsbourger, L. Li, V. Picheny, and E. Vazquez, Sequential design of computer experiments for the estimation of a probability of failure, Statistics and Computing, vol.34, issue.4, 2012.
DOI : 10.1007/s11222-011-9241-4
URL : https://hal.archives-ouvertes.fr/hal-00689580

K. Campbell, M. D. Mckay, and B. J. Williams, Sensitivity analysis when model outputs are functions, Reliability Engineering & System Safety, vol.91, issue.10-11, pp.1468-1472, 2006.
DOI : 10.1016/j.ress.2005.11.049

A. De-crécy, Determination of the uncertainties of the constitutive relationships of the CATHARE 2 code, M&C 2001, 2001.

A. De-crécy, P. Bazin, H. Glaeser, T. Skorek, J. Joucla et al., Uncertainty and sensitivity analysis of the LOFT L2-5 test: Results of the BEMUSE programme, Nuclear Engineering and Design, vol.238, issue.12, pp.3561-3578, 2008.
DOI : 10.1016/j.nucengdes.2008.06.004

E. De-rocquigny, La ma??trisema??trise des incertitudes dans un contexte industriel -1` ere partie : une approche méthodologique globale basée sur des exemples, Journal de la Société Française de Statistique, pp.33-71, 2006.

A. Dean and S. Lewis, Screening -Methods for experimentation in industry, drug discovery and genetics, 2006.

K. Fang, R. Li, and A. Sudjianto, Design and modeling for computer experiments, 2006.
DOI : 10.1201/9781420034899

J. H. Friedman and W. Stuetzle, Projection Pursuit Regression, Journal of the American Statistical Association, vol.4, issue.376, pp.817-823, 1981.
DOI : 10.1080/01621459.1981.10477729
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.382.4593

J. C. Helton, J. D. Johnson, C. J. Salaberry, and C. B. Storlie, Survey of sampling-based methods for uncertainty and sensitivity analysis, Reliability Engineering & System Safety, vol.91, issue.10-11, pp.1175-1209, 2006.
DOI : 10.1016/j.ress.2005.11.017

B. Iooss, L. Boussouf, V. Feuillard, and A. Marrel, Numerical studies of the metamodel fitting and validation processes, International Journal of Advances in Systems and Measurements, vol.3, pp.11-21, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00444666

B. Iooss, F. Van-dorpe, and N. Devictor, Response surfaces and sensitivity analyses for an environmental model of dose calculations, Reliability Engineering & System Safety, vol.91, issue.10-11, pp.1241-1251, 2006.
DOI : 10.1016/j.ress.2005.11.021

J. P. Kleijnen, Design and analysis of simulation experiments, 2008.
DOI : 10.1007/978-3-319-18087-8

M. Lamboni, D. Makowski, S. Lehuger, B. Gabrielle, and H. Monod, Multivariate global sensitivity analysis for dynamic crop models, Field Crops Research, vol.113, issue.3, pp.312-320, 2009.
DOI : 10.1016/j.fcr.2009.06.007
URL : https://hal.archives-ouvertes.fr/hal-01173193

M. Lamboni, H. Monod, and D. Makowski, Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models, Reliability Engineering & System Safety, vol.96, issue.4, pp.450-459, 2011.
DOI : 10.1016/j.ress.2010.12.002
URL : https://hal.archives-ouvertes.fr/hal-00999840

T. Lin, H. Zha, and S. U. Lee, Riemannian Manifold Learning for Nonlinear Dimensionality Reduction, 9th European Conference on Computer Vision, pp.44-55, 2006.
DOI : 10.1007/11744023_4

M. Marqù-es, J. F. Pignatel, P. Saignes, F. D-'auria, L. Burgazzi et al., Methodology for the reliability evaluation of a passive system and its integration into a Probabilistic Safety Assessment, Nuclear Engineering and Design, vol.235, issue.24, pp.2612-2631, 2005.
DOI : 10.1016/j.nucengdes.2005.06.008

A. Marrel, B. Iooss, M. Jullien, B. Laurent, and E. Volkova, Global sensitivity analysis for models with spatially dependent outputs, Environmetrics, vol.34, issue.1, pp.383-397, 2011.
DOI : 10.1002/env.1071
URL : https://hal.archives-ouvertes.fr/hal-00430171

D. C. Montgomery, Design and analysis of experiments, 2004.

M. Munoz-zuniga, J. Garnier, E. Remy, and E. De-rocquigny, Adaptive directional stratification for controlled estimation of the probability of a rare event, Reliability Engineering and System Safety, 2010.

J. O. Ramsay and B. W. Silverman, Functional Data Analysis, 2005.

V. Roth, T. Lange, M. Braun, and J. Buhmann, A Resampling Approach to Cluster Validation, International Conference on Computational Statistics, pp.123-128, 2002.
DOI : 10.1007/978-3-642-57489-4_13

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 and P. Annoni, How to avoid a perfunctory sensitivity analysis. Environmental Modelling and Software, pp.1508-1517, 2010.

A. Saltelli, M. Ratto, T. Andres, F. Campolongo, J. Cariboni et al., Global sensitivity analysis -The primer, 2008.
DOI : 10.1002/9780470725184

I. M. Sobol, Sensitivity estimates for non linear mathematical models, Mathematical Modelling and Computational Experiments, vol.1, pp.407-414, 1993.

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, Stochastic Environmental Research and Risk Assessment, vol.16, issue.1, pp.17-31, 2008.
DOI : 10.1007/s00477-006-0093-y

L. Yen, D. Vanvyve, F. Wouters, F. Fouss, M. Verleysen et al., Clustering using a random-walk based distance measure, Symposium on Artificial Neural Networks, pp.317-324, 2005.