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Optimal designs for generalized linear models

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Summary

This paper solves some D-optimal design problems for certain Generalized Linear Models where the mean depends on two parameters and two explanatory variables. In all of the cases considered the support point of the optimal designs are found to be independent of the unknown parameters. While in some cases the optimal design measures are given by two points with equal weights, in others the support is given by three point with weights depending on the unknown parameters, hence the designs are locally optimal in general. Empirical results on the efficiency of the locally optimal designs are also given. Some of the designs found can also be used for planning D-optimal experiments for the normal linear model, where the mean must be positive.

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Authors and Affiliations

  1. Dept. Statistical Science, University College of London, Gower Street WC1E 6BT, London, England

    J. Burridge

  2. Dip. Scienze Statistiche, Università di Perugia, Via Pascoli, Perugia, Italy

    P. Sebastiani

Authors
  1. J. Burridge
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  2. P. Sebastiani
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Additional information

This research was carried out in part at University College, London as an M.Sc. project. Thanks are due to Prof. I. Ford (University of Glasgow) and Prof. A. Giovagnoli (University of Perugia) for their valuable suggestions and critical observations.

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Burridge, J., Sebastiani, P. Optimal designs for generalized linear models. J. It. Statist. Soc. 1, 183–202 (1992). https://doi.org/10.1007/BF02589030

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  • DOI: https://doi.org/10.1007/BF02589030

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