Abstract
We consider the problem of finding an optimal design under a Poisson regression model with a log link, any number of independent variables, and an additive linear predictor. Local D-optimality of a class of designs is established through use of a canonical form of the problem and a general equivalence theorem. The results are applied in conjunction with clustering techniques to obtain a fast method of finding designs that are robust to wide ranges of model parameter values. The methods are illustrated through examples.
Original language | English |
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Pages (from-to) | 721-730 |
Number of pages | 10 |
Journal | Statistica Sinica |
Volume | 19 |
Issue number | 2 |
Publication status | Published - Apr 2009 |