Response surface design evaluation and comparison, Journal of Statistical Planning and Inference, vol.139, issue.2, pp.629-641, 2009. ,
DOI : 10.1016/j.jspi.2008.04.004
Achieving Robust Design from Computer Simulations, Quality Technology & Quantitative Management, vol.3, issue.2, pp.161-177, 2006. ,
DOI : 10.1080/16843703.2006.11673107
Computer model validation with functional output. The Annals of Statistics, pp.1874-1906, 2007. ,
Learning heteroscedastic Gaussian processes for complex datasets, 2009. ,
Screening experiments for dispersion effects, editors, Screening -Methods for experimentation in industry , drug discovery and genetics, 2006. ,
A review on design, modeling and applications of computer experiments, IIE Transactions, vol.19, issue.4, pp.273-291, 2006. ,
DOI : 10.2307/2670057
Uncertainty in industrial practice, 2008. ,
DOI : 10.1002/9780470770733
Design and modeling for computer experiments, 2006. ,
DOI : 10.1201/9781420034899
Kriging with heterogeneous nugget effect for the approximation of noisy simulators with tunable fidelity, Proceedings of Joint Meeting of the Statistical Society of Canada and the Socit Franaise de Statistique, 2008. ,
URL : https://hal.archives-ouvertes.fr/hal-00409766
Generalized additive models, 1990. ,
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
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
Treatment of spatially dependent variables in sensitivity analysis of model output methods, Note Technique CEA, 2008. ,
Numerical simulation of transit-time ultrasonic flowmeters: uncertainties due to flow profile and fluid turbulence, Ultrasonics, vol.40, issue.9, pp.1009-1015, 2002. ,
DOI : 10.1016/S0041-624X(02)00387-6
Analyse de sensibilité globale de modèles numériquesnumériques`numériquesà paramètres incontrôlables, Proceedings of 38èmes Journées de Statistique, 2006. ,
Global sensitivity analysis of computer models with functional inputs, Reliability Engineering & System Safety, vol.94, issue.7, pp.1194-1204, 2009. ,
DOI : 10.1016/j.ress.2008.09.010
URL : https://hal.archives-ouvertes.fr/hal-00243156
A comparaison of methods for joint modelling of mean and dispersion, Proceedings of the 11th Symposium on ASMDA, 2005. ,
Bayesian calibration of computer models, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.3, pp.425-464, 2001. ,
DOI : 10.1111/1467-9868.00294
Sensitivity analysis and related analyses: A review of some statistical techniques, Journal of Statistical Computation and Simulation, vol.1, issue.1-4, pp.111-142, 1997. ,
DOI : 10.2307/1266728
Robustness of Kriging when interpolating in random simulation with heterogeneous variances: Some experiments, European Journal of Operational Research, vol.165, issue.3, pp.826-834, 2005. ,
DOI : 10.1016/j.ejor.2003.09.037
Robust design via generalized linear models, Journal of Quality Technology, vol.35, issue.1, pp.2-12, 2003. ,
Choosing the Sample Size of a Computer Experiment: A Practical Guide, National Institute of Statistical Sci- ences, 2008. ,
DOI : 10.1198/TECH.2009.08040
An efficient methodology for modeling complex computer codes with Gaussian processes, Computational Statistics & Data Analysis, vol.52, issue.10, pp.4731-4744, 2008. ,
DOI : 10.1016/j.csda.2008.03.026
URL : https://hal.archives-ouvertes.fr/hal-00239492
Generalized linear models, 1989. ,
A large class of models derived from generalized linear models, Statistics in Medicine, vol.17, issue.23, pp.2747-2753, 1998. ,
DOI : 10.1002/(SICI)1097-0258(19981215)17:23<2747::AID-SIM40>3.0.CO;2-I
An extended quasi-likelihood function, Biometrika, vol.74, issue.2, pp.221-232, 1987. ,
DOI : 10.1093/biomet/74.2.221
Generalized Linear Models, Journal of the Royal Statistical Society. Series A (General), vol.135, issue.3, pp.370-384, 1972. ,
DOI : 10.2307/2344614
Quality engineering using robust design, 1989. ,
Review: P. McCullagh, J. A. Nelder, Generalized Linear Models, The Annals of Statistics, vol.12, issue.4, pp.1589-1596, 1984. ,
DOI : 10.1214/aos/1176346819
R: A Language and Environment for Statistical Computing, 2006. ,
A semi-parametric additive model for variance heterogeneity, Statistics and Computing, vol.55, issue.1, pp.57-65, 1996. ,
DOI : 10.1007/BF00161574
Design and Analysis of Computer Experiments, Statistical Science, vol.4, issue.4, pp.409-435, 1989. ,
DOI : 10.1214/ss/1177012413
Sensitivity analysis, 2000. ,
URL : https://hal.archives-ouvertes.fr/inria-00386559
Generalized linear models with varying dispersion, Journal of the Royal Statistical Society B, vol.51, pp.47-60, 1989. ,
Sensitivity estimates for non linear mathematical models, Mathematical Modelling and Computational Experiments, vol.1, pp.407-414, 1993. ,
Combining Taguchi and response-surface philosophies -a dual response approach, Journal of Quality Technology, vol.22, pp.38-45, 1990. ,
Global sensitivity analysis for a numerical model of radionuclide migration from the RRC ???Kurchatov Institute??? radwaste disposal site, Stochastic Environmental Research and Risk Assesment, pp.17-31, 2008. ,
DOI : 10.1007/s00477-006-0093-y
GAMs with integrated model selection using penalized regression splines and applications to environmental modelling, Ecological Modelling, vol.157, issue.2-3, pp.157-177, 2002. ,
DOI : 10.1016/S0304-3800(02)00193-X
Prediction and Density Estimation of a Horizontal Well Productivity Index Using Generalized Linear Models, ECMOR VI, 6th European Conference on the Mathematics of Oil Recovery, 1998. ,
DOI : 10.3997/2214-4609.201406664