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D-optimal designs for polynomial regression models through origin

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  • Fang, Zhide
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    Abstract

    In this article we consider D-optimal designs for polynomial regression models with low-degree terms being missed, by applying the theory of canonical moments. It turns out that the optimal design places equal weight on each of the zeros of some Jacobi polynomial when the number of unknown parameters in the model is even. The procedure and examples of finding the optimal supports and weights are given when the number of unknown parameters in the model is odd.

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    Bibliographic Info

    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 57 (2002)
    Issue (Month): 4 (May)
    Pages: 343-351

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    Handle: RePEc:eee:stapro:v:57:y:2002:i:4:p:343-351

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    Related research

    Keywords: Polynomial regression Jacobi polynomials Canonical moments Hankel determinant Regression through the origin;

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    Cited by:
    1. Fang, Zhide, 2003. "D-optimal designs for weighted polynomial regression," Statistics & Probability Letters, Elsevier, vol. 63(2), pages 205-213, June.
    2. Kim-Hung Li & Tai-Shing Lau & Chongqi Zhang, 2005. "A note on D-optimal designs for models with and without an intercept," Statistical Papers, Springer, vol. 46(3), pages 451-458, July.

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