Management Science
The spatial correlation function approach to response surface estimation
WSC '92 Proceedings of the 24th conference on Winter simulation
Metamodeling for cycle time-throughput-product mix surfaces using progressive model fitting
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Stochastic Kriging for Simulation Metamodeling
Operations Research
Discrete-Time Signal Processing
Discrete-Time Signal Processing
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The correlation function plays a critical role in both kriging and stochastic kriging metamodels. This paper will compare various correlation functions in both spatial and frequency domains, and analyze the influence of the choice of correlation function on prediction accuracy by experimenting with three tractable examples with differentiable and non-differentiable response surfaces: the M/M/1 queue, multi-product M/G/1 queue and 3-station Jackson network. The twice or higher-order continuously differentiable correlation functions demonstrate a promising capability to fit both differentiable and non-differentiable multi-dimensional response surfaces.