Robust Designs For Binary Data: Applications Of Simulated Annealing

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Description/Abstract

When the aim of an experiment is the estimation of a Generalised Linear Model (GLM), standard designs
from linear model theory may prove inadequate. This paper describes a flexible approach for finding
designs for experiments to estimate GLMs through the use of D-optimality and a simulated annealing
algorithm. A variety of uncertainties in the model can be incorporated into the design search, including
the form of the linear predictor, through use of a robust design selection criterion and a postulated
model space. New methods appropriate for screening experiments and the incorporation of correlations
between possible model parameters are described through examples. An updating formula for Doptimality
under a GLM is presented which improves the computational efficiency of the search.