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Prediction for computer experiments with both quantitative and qualitative factors

Author

Listed:
  • Li, Min
  • Liu, Min-Qian
  • Wang, Xiao-Lei
  • Zhou, Yong-Dao

Abstract

Computer experiments with both quantitative and qualitative factors are commonly encountered in practice. Several literatures found that if the cross-correlation between an auxiliary response and the target response (i.e., the response to be predicted) is small, the information of such an auxiliary response may reduce the prediction accuracy of the target response. In this work, we use the prediction accuracy improvement probability to prove the possibility of this case in theory and develop a selection procedure to choose the useful auxiliary responses.

Suggested Citation

  • Li, Min & Liu, Min-Qian & Wang, Xiao-Lei & Zhou, Yong-Dao, 2020. "Prediction for computer experiments with both quantitative and qualitative factors," Statistics & Probability Letters, Elsevier, vol. 165(C).
    • Handle: RePEc:eee:stapro:v:165:y:2020:i:c:s0167715220301619
    DOI: 10.1016/j.spl.2020.108858
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    References listed on IDEAS

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    1. Peter Z. G. Qian, 2012. "Sliced Latin Hypercube Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 393-399, March.
    2. Bao, Yong & Kan, Raymond, 2013. "On the moments of ratios of quadratic forms in normal random variables," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 229-245.
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