Pages that link to "Item:Q1595979"

The following pages link to Design and analysis of computer experiments. With comments and a rejoinder by the authors (Q1595979):

Displaying 50 items.

• Verifying reification with application to a rainfall-runoff computer simulator (Q2261041) (← links)
• One-dimensional nested maximin designs (Q2269596) (← links)
• Batch sequential designs for computer experiments (Q2270267) (← links)
• Kernel interpolation (Q2275648) (← links)
• Airfoil optimization design based on the pivot element weighting iterative method (Q2283830) (← links)
• A survey on kriging-based infill algorithms for multiobjective simulation optimization (Q2289950) (← links)
• Shape optimization of a cyclone separator using multi-objective surrogate-based optimization (Q2290582) (← links)
• High dimensional kriging metamodelling utilising gradient information (Q2290871) (← links)
• Financial and risk modelling with semicontinuous covariances (Q2293145) (← links)
• Sparse regression Chebyshev polynomial interval method for nonlinear dynamic systems under uncertainty (Q2294778) (← links)
• Estimates of the coverage of parameter space by Latin hypercube and orthogonal array-based sampling (Q2295290) (← links)
• Stratified random sampling for dependent inputs in Monte Carlo simulations from computer experiments (Q2301061) (← links)
• Iterative construction of Gaussian process surrogate models for Bayesian inference (Q2301102) (← links)
• Global fitting of the response surface via estimating multiple contours of a simulator (Q2301224) (← links)
• Versatile sequential sampling algorithm using kernel density estimation (Q2301957) (← links)
• A multiobjective stochastic simulation optimization algorithm (Q2301958) (← links)
• A modern retrospective on probabilistic numerics (Q2302460) (← links)
• Inverse regression for ridge recovery: a data-driven approach for parameter reduction in computer experiments (Q2302488) (← links)
• Nonparametric estimation of probabilistic sensitivity measures (Q2302500) (← links)
• Robust additive Gaussian process models using reference priors and cut-off-designs (Q2307104) (← links)
• Sequential approximate optimization for design under uncertainty problems utilizing Kriging metamodeling in augmented input space (Q2308910) (← links)
• An estimation algorithm for fast Kriging surrogates of computer models with unstructured multiple outputs (Q2309874) (← links)
• A near-stationary subspace for ridge approximation (Q2310068) (← links)
• Optimization of expensive black-box problems via gradient-enhanced Kriging (Q2310272) (← links)
• A screening-based gradient-enhanced Kriging modeling method for high-dimensional problems (Q2310508) (← links)
• Modified screening-based kriging method with cross validation and application to engineering design (Q2310626) (← links)
• Efficient evaluation of reliability-oriented sensitivity indices (Q2316182) (← links)
• Jointly robust prior for Gaussian stochastic process in emulation, calibration and variable selection (Q2316987) (← links)
• A unified approach to environmental systems modeling (Q2319553) (← links)
• Conditional quantile sequential estimation for stochastic codes (Q2321791) (← links)
• Maximum likelihood estimation for Gaussian processes under inequality constraints (Q2323946) (← links)
• A supermartingale approach to Gaussian process based sequential design of experiments (Q2325344) (← links)
• Comment: unreasonable effectiveness of Monte Carlo (Q2325607) (← links)
• Rates of contraction with respect to \(L_2\)-distance for Bayesian nonparametric regression (Q2326065) (← links)
• Gauss-Christoffel quadrature for inverse regression: applications to computer experiments (Q2329776) (← links)
• Asymptotic analysis of the learning curve for Gaussian process regression (Q2339938) (← links)
• Uncertainty quantification for functional dependent random variables (Q2358935) (← links)
• Exploring multi-stage shape optimization strategy of multi-body geometries using Kriging-based model and adjoint method (Q2361949) (← links)
• Fixed-domain asymptotics for a subclass of Matérn-type Gaussian random fields (Q2368857) (← links)
• Full scale multi-output Gaussian process emulator with nonseparable auto-covariance functions (Q2374734) (← links)
• Gaussian process surrogates for failure detection: a Bayesian experimental design approach (Q2375069) (← links)
• An overview of the design and analysis of simulation experiments for sensitivity analysis (Q2387211) (← links)
• Default priors for Gaussioan processes (Q2388348) (← links)
• Derivative-free optimization: a review of algorithms and comparison of software implementations (Q2392129) (← links)
• A quasi-multistart framework for global optimization of expensive functions using response surface models (Q2393073) (← links)
• Pseudo expected improvement criterion for parallel EGO algorithm (Q2399490) (← links)
• Gaussian process emulators for computer experiments with inequality constraints (Q2399826) (← links)
• Cross-validation estimation of covariance parameters under fixed-domain asymptotics (Q2401354) (← links)
• A Bayesian approach to the selection of two-level multi-stratum factorial designs (Q2413609) (← links)
• Selection of a covariance function for a Gaussian random field aimed for modeling global optimization problems (Q2414108) (← links)