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K-optimal designs for the second-order Scheffé polynomial model

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  • Haosheng Jiang
  • Chongqi Zhang
  • Jiali Chen

Abstract

The K-optimality criterion is proposed to avoid multicollinearity in regression analysis. By far the most, popular models for modeling the response of a mixture experiment are the Scheffé polynomial models. The Scheffé polynomial models have a small degree of multicollinearity. However, there have been no reports about constructing K-optimal designs for the Scheffé polynomial models. This article expands the K-optimality criterion to the second-order Scheffé polynomial model, and derives the K-optimal allocations for such model. We also investigate the construction method of K-optimal designs with the non linear constraints. In addition, the relative efficiencies of D-, A-, and K-optimal designs are compared.

Suggested Citation

  • Haosheng Jiang & Chongqi Zhang & Jiali Chen, 2024. "K-optimal designs for the second-order Scheffé polynomial model," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 53(22), pages 8127-8139, November.
    • Handle: RePEc:taf:lstaxx:v:53:y:2024:i:22:p:8127-8139
    DOI: 10.1080/03610926.2023.2279914
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