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On the equivalence of D and G-optimal designs in heteroscedastic models

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  • Wong, Weng Kee

Abstract

Conditions are derived for the Kiefer-Wolfowitz's theorem (KWT) to apply to linear models with heteroscedastic errors. It is shown that both D- and G-optimal designs remain equivalent only under very stringent conditions. Examples are constructed and their efficiencies are compared when they are not equivalent. For the simple linear regression model with a symmetric efficiency function, a relationship between the efficiencies of the optimal designs and the support points of the D-optimal design is noted.

Suggested Citation

  • Wong, Weng Kee, 1995. "On the equivalence of D and G-optimal designs in heteroscedastic models," Statistics & Probability Letters, Elsevier, vol. 25(4), pages 317-321, December.
    • Handle: RePEc:eee:stapro:v:25:y:1995:i:4:p:317-321
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    1. Wong, Weng Kee, 1993. "Minimal number of support points for mini-max optimal designs," Statistics & Probability Letters, Elsevier, vol. 17(5), pages 405-409, August.
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    Cited by:

    1. Min-Jue Zhang & Rong-Xian Yue, 2020. "Locally D-optimal designs for heteroscedastic polynomial measurement error models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(6), pages 643-656, August.
    2. Prus, Maryna, 2019. "Various optimality criteria for the prediction of individual response curves," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 36-41.

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