Computer experiments: design, modeling and integration

The use of computer modeling is fast increasing in almost everyscientific, engineering and business arena. This dissertationinvestigates some challenging issues in design, modeling andanalysis of computer experiments, which will consist of four majorparts. In the first part, a new approach is developed to combinedata from approximate and detailed simulations to build asurrogate model based on some stochastic models. In the secondpart, we propose some Bayesian hierarchical Gaussian processmodels to integrate data from different types of experiments. Thethird part concerns the development of latent variable models forcomputer experiments with multivariate response with applicationto data center temperature modeling. The last chapter is devotedto the development of nested space-filling designs for multipleexperiments with different levels of accuracy.