Robust designs for binary data: applications of simulated annealing

• Published in: Journal of statistical computation and simulation Vol. 80; no. 1; pp. 29 - 41
• Main Author: Woods, D. C.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 01.01.2010; Taylor & Francis Ltd
• Subjects: Binary system; Computational efficiency; Computer simulation; Criteria; Generalized linear models; Mathematical models; optimal design; prior information; Regression analysis; Screening; screening experiments; Searching; Simulated annealing; Simulation
• ISSN: 0094-9655; 1563-5163
• DOI: 10.1080/00949650802445367

When the aim of an experiment is the estimation of a generalized 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 using examples. An updating formula for D-optimality under a GLM is presented, which improves the computational efficiency of the search.