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Computer Experiments with Qualitative and Quantitative Variables: A Review and Reexamination

Summary: [This abstract is based on the authors' abstract.] This article reviews and reexamines approaches to modeling computer experiments with qualitative and quantitative input variables. For those not familiar with models for computer experiments, the authors begin by showing, in a simple setting, that a standard model for computer experiments can be viewed as a generalization of regression models. The article then reviews models that include both quantitative and quantitative variables and presents some alternative parameterizations. Two are based on indicator functions and allow one to use standard quantitative inputs-only models. Another parameterization provides additional insight into possible underlying factorial structure. Finally, the authors use two examples to illustrate the benefits of these alternative models. The article includes an explanation of the Gaussian stochastic process (GaSP) model.

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  • Topics: Statistical Process Control (SPC)
  • Keywords: Computer models, Variable data, Statistical experimental design (SED), Gaussian curve, Stochastic models, Prediction, Correlated data, Factorial experiments, Indicators, Parameter design
  • Author: Zhang, Yulei; Notz, William I.;
  • Journal: Quality Engineering