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A note on maximin and Bayesian D-optimal designs in weighted polynomial regression

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  • Biedermann, Stefanie
  • Dette, Holger

Abstract

We consider the problem of finding D-optimal designs for estimating the coefficients in a weighted polynominal regression model with a certain efficiency function depending on two unknown parameters, which models he heteroscedastic error structure. This problem is tackled by adopting a Bayesian and a maximin approach, and optimal designs supported on a minimal number of support points are determined explicitly.

Suggested Citation

  • Biedermann, Stefanie & Dette, Holger, 2003. "A note on maximin and Bayesian D-optimal designs in weighted polynomial regression," Technical Reports 2003,03, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200303
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    Cited by:

    1. Dette, Holger & Haines, Linda M. & Imhof, Lorens A., 2003. "Bayesian and maximin optimal designs for heteroscedastic regression models," Technical Reports 2003,36, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

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