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Optimal minimax designs over a prespecified interval in a heteroscedastic polynomial model

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  • Chen, Ray-Bing
  • Wong, Weng Kee
  • Li, Kun-Yu

Abstract

Minimax optimal designs can be useful for estimating response surface but they are notoriously difficult to study analytically. We provide the formulae for three types of minimax optimal designs over a user-specified region. We focus on polynomial models with various types of heteroscedastic errors but the design strategy is applicable to other types of linear models and optimality criteria. Relationships among the three types of minimax optimal designs are discussed.

Suggested Citation

  • Chen, Ray-Bing & Wong, Weng Kee & Li, Kun-Yu, 2008. "Optimal minimax designs over a prespecified interval in a heteroscedastic polynomial model," Statistics & Probability Letters, Elsevier, vol. 78(13), pages 1914-1921, September.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:13:p:1914-1921
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    References listed on IDEAS

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    1. Holger Dette & Mong-Na Lo Huang, 2000. "Convex Optimal Designs for Compound Polynomial Extrapolation," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 52(3), pages 557-573, September.
    2. Huang, Mong-Na Lo, 1990. "Optimal extrapolation designs for a partly linear model," Computational Statistics & Data Analysis, Elsevier, vol. 10(2), pages 109-115, October.
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    Cited by:

    1. Hooshangifar, M. & Talebi, H., 2021. "Bayesian optimal design for non-linear model under non-regularity condition," Statistics & Probability Letters, Elsevier, vol. 169(C).

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