IDEAS home Printed from
   My bibliography  Save this article

Efficient discriminating design for a class of nested polynomial regression models


  • Min-Hsiao Tsai



This paper studies efficient designs for simultaneous model discrimination among polynomial regression models up to degree k. Based on the $${\Phi_{\boldsymbol{\beta}}}$$ -optimality criterion proposed by Dette (Ann Stat 22:890–903, 1994 ), a maximin $${\Phi_{\boldsymbol{\beta}^{*}}}$$ -optimal discriminating design is derived in terms of canonical moments for $${k\in\mathbb{N}}$$ . Theoretical and numerical results show that the proposed design performs well for model discrimination in most of the considered models. Copyright Springer-Verlag 2012

Suggested Citation

  • Min-Hsiao Tsai, 2012. "Efficient discriminating design for a class of nested polynomial regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(6), pages 809-817, August.
  • Handle: RePEc:spr:metrik:v:75:y:2012:i:6:p:809-817
    DOI: 10.1007/s00184-011-0353-9

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Dette, Holger & Franke, Tobias, 2000. "Constrained D- and D1-optimal designs for polynomial regression," Technical Reports 2000,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    2. Stefanie Biedermann & Holger Dette & Philipp Hoffmann, 2009. "Constrained optimal discrimination designs for Fourier regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 143-157, March.
    Full references (including those not matched with items on IDEAS)


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:metrik:v:75:y:2012:i:6:p:809-817. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.