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Computer Experiments With Both Qualitative and Quantitative Variables

Summary: Computer experiments have received a great deal of attention in many fields of science and technology. Most literature assumes that all the input variables are quantitative. However, researchers often encounter computer experiments involving both qualitative and quantitative variables (BQQV). In this article, a new interface on design and analysis for computer experiments with BQQV is proposed. The new designs are one kind of sliced Latin hypercube designs with points clustered in the design region and possess good uniformity for each slice. For computer experiments with BQQV, such designs help to measure the similarities among responses of different level-combinations in the qualitative variables. An adaptive analysis strategy intended for the proposed designs is developed. The proposed strategy allows us to automatically extract information from useful auxiliary responses to increase the precision of prediction for the target response. The interface between the proposed design and the analysis strategy is demonstrated to be effective via simulation and a real-life example from the food engineering literature. Supplementary materials for this article are available online.

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  • Topics: Design of Experiments, Software and Technology (for statistics, measurement, analysis), Statistics
  • Keywords: Cross-validation, Gaussian process model, Kriging, Latin hypercube design, Similarity
  • Author: Huang, Hengzhen; Lin, Dennis K. J.; Liu, Min-Qian; Yang, Jian-Feng
  • Journal: Technometrics