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On Optimal Designs for High Dimensional Binary Regression Models

  • Ben Torsney
  • Necla Gunduz
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 51)

Abstract

We consider the problem of deriving optimal designs for generalised linear models depending on several design variables. Ford, Torsney and Wu (1992) consider a two parameter/single design variable case. They derive a range of optimal designs, while making conjectures about D-optimal designs for all possible design intervals in the case of binary regression models. Motivated by these we establish results concerning the number of support points in the multi-design-variable case, an area which, in respect of non-linear models, has uncharted prospects.

Keywords

binary response models binary weight functions D-Optimal generalized linear model weighted linear regression 

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Copyright information

© Springer Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Ben Torsney
    • 1
  • Necla Gunduz
    • 2
  1. 1.Department of StatisticsUniversity of GlasgowScotland, UK
  2. 2.Department of StatisticsUniversity of GaziAnkaraTurkey

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