Stochastic Kriging for Simulation Metamodeling, Operations Research, vol.58, issue.2, pp.371-382, 2010. ,
DOI : 10.1287/opre.1090.0754
Computer model validation with functional output. The Annals of Statistics, pp.1874-1906, 2007. ,
Learning heteroscedastic Gaussian processes for complex datasets, Neural Computing Research Group, 2009. ,
Screening experiments for dispersion effects, editors, Screening -Methods for experimentation in industry, drug discovery and genetics, 2006. ,
Chiì es, Geostatistics: Modeling spatial uncertainty Robust optimization in simulation: Taguchi and Response Surface Methodology, IIE Transactions International Journal of Production Economics, vol.38, issue.125, pp.273-29152, 1999. ,
Uncertainty in industrial practice, 2008. ,
DOI : 10.1002/9780470770733
Design and modeling for computer experiments, 2006. ,
DOI : 10.1201/9781420034899
Design and Analysis of "Noisy" Computer Experiments, AIAA Journal, vol.44, issue.10, pp.2331-2339, 2006. ,
DOI : 10.2514/1.20068
Nonparametric estimation of mean and dispersion functions in extended generalized linear models, TEST, vol.36, issue.3, pp.580-608, 2010. ,
DOI : 10.1007/s11749-010-0187-1
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 Société Franaise de Statistique, 2008. ,
URL : https://hal.archives-ouvertes.fr/hal-00409766
Bayesian Treed Gaussian Process Models With an Application to Computer Modeling, Journal of the American Statistical Association, vol.103, issue.483, pp.1119-1130, 2008. ,
DOI : 10.1198/016214508000000689
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
Conceptual and computational basis for the quantification of margins and uncertainty . Sandia National Laboratories, 2009. ,
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
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
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
Simulation with Arena; fourth edition, 2007. ,
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
Most likely heteroscedastic Gaussian process regression, Proceedings of the 24th international conference on Machine learning, ICML '07, 2007. ,
DOI : 10.1145/1273496.1273546
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.476.7182
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
Design and analysis of simulation experiments, 2008. ,
DOI : 10.1007/978-3-319-18087-8
Robust design via generalized linear models, Journal of Quality Technology, vol.35, issue.1, pp.2-12, 2003. ,
Combination of Experimental Design and Joint Modeling Methods for Quantifying the Risk Associated With Deterministic and Stochastic Uncertainties - An Integrated Test Study, SPE Annual Technical Conference and Exhibition, 2001. ,
DOI : 10.2118/71620-MS
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
Use of Kriging Models to Approximate Deterministic Computer Models, AIAA Journal, vol.43, issue.4, pp.853-863, 2005. ,
DOI : 10.2514/1.8650
Generalized linear models, 1989. ,
Response surface methodology: process and product optimization using designed experiments An extended quasi-likelihood function, Biometrika, vol.74, pp.221-232, 1987. ,
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. ,
Optimization of noisy computer experiments with tunable precision, Technometrics, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00578550
Lagrangian PDF Methods for Turbulent Flows, Annual Review of Fluid Mechanics, vol.26, issue.1, pp.23-63, 1994. ,
DOI : 10.1146/annurev.fl.26.010194.000323
Variable selection for Bayesian density estimation: Application to human exposure simulation, Environmental and Ecological Statistics, 2009. ,
A semi-parametric approach to dual modeling when no replication exists, Journal of Statistical Planning and Inference, vol.140, issue.10, pp.2860-2869, 2010. ,
DOI : 10.1016/j.jspi.2010.03.009
Hydrocarbon exploration risk evaluation through uncertainty and sensitivity analyses techniques, Reliability Engineering & System Safety, vol.91, issue.10-11, pp.1155-1162, 2006. ,
DOI : 10.1016/j.ress.2005.11.056
Design and Analysis of Computer Experiments, Statistical Science, vol.4, issue.4, pp.409-435, 1989. ,
DOI : 10.1214/ss/1177012413
Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index, Computer Physics Communications, vol.181, issue.2, pp.259-270, 2010. ,
DOI : 10.1016/j.cpc.2009.09.018
Sensitivity analysis, 2000. ,
URL : https://hal.archives-ouvertes.fr/inria-00386559
Discrete-event simulation is dead, long live agent-based simulation!, Journal of Simulation, vol.31, issue.3, pp.204-210, 2010. ,
DOI : 10.1093/acprof:oso/9780195172119.001.0001
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. ,
Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models, Reliability Engineering and System Safety, pp.1735-1763, 2009. ,
DOI : 10.1016/j.ress.2009.05.007
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
Bayesian-Validated Surrogates for Noisy Computer Simulations; Application to Random Media, SIAM Journal on Scientific Computing, vol.17, issue.4, pp.973-992, 1996. ,
DOI : 10.1137/0917063
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
A new approach for quantifying the impact of geostatistical uncertainty on production forecasts: The joint modeling method, Proceedings of IAMG Conference, 2001. ,
Uncertainty management: From geological scenarios to production scheme optimization, Journal of Petroleum Science and Engineering, vol.44, issue.1-2, pp.11-25, 2004. ,
DOI : 10.1016/j.petrol.2004.02.002