Multiplicative algorithms for computing optimum designs

We study a new approach to determine optimal designs, exact or approximate, both for the uncorrelated case and when the responses may be correlated. A simple version of this method is based on transforming design points on a finite interval to proportions of the interval. Methods for determining opt...

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Bibliographic Details
Published in:Journal of statistical planning and inference 2009-12, Vol.139 (12), p.3947-3961
Main Authors: Torsney, B., Martín-Martín, R.
Format: Article
Language:English
Subjects:
Approximate design
Combinatorics
Combinatorics. Ordered structures
Covariance function
Designs and configurations
Exact design
Exact sciences and technology
Experimental design
General topics
Mathematics
Multiplicative algorithm
Multivariate analysis
Probability and statistics
Sciences and techniques of general use
Statistics
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Summary:We study a new approach to determine optimal designs, exact or approximate, both for the uncorrelated case and when the responses may be correlated. A simple version of this method is based on transforming design points on a finite interval to proportions of the interval. Methods for determining optimal design weights can therefore be used to determine optimal values of these proportions. We explore the potential of this method in a range of examples encompassing linear and non-linear models, some assuming a correlation structure and some with more than one design variable.
ISSN:0378-3758
1873-1171
DOI:10.1016/j.jspi.2009.05.007