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Journal of Statistical Theory and Practice

, Volume 5, Issue 1, pp 137–145 | Cite as

Continuous Optimal Designs for Generalized Linear Models under Model Uncertainty

  • D. C. WoodsEmail author
  • S. M. Lewis
Article

Abstract

We propose a general design selection criterion for experiments where a generalized linear model describes the response. The criterion allows for several competing aims, such as parameter estimation and model discrimination, and also for uncertainty in the functional form of the linear predictor, the link function and the unknown model parameters. A general equivalence theorem is developed for this criterion. In practice, an exact design is required by experimenters and can be obtained by numerical rounding of a continuous design. We derive bounds on the performance of an exact design under this criterion which allow the efficiency of a rounded continuous design to be assessed.

Key-words

Exponential family General equivalence theorem Logistic regression Nonlinear regression Optimal design 

AMS Subject Classification

62K05 62J12 

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Copyright information

© Grace Scientific Publishing 2011

Authors and Affiliations

  1. 1.Southampton Statistical Sciences Research InstituteUniversity of SouthamptonSouthamptonUK

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