A new algorithm for optimal, distance based, experimental design is presented. The proposed approach, in contrast to other optimality criteria, does not require any preliminary hypothesis about a regression model. The best set of experiments is defined through a fast exchange algorithm where, in each cycle, a substitution is selected to provide the maximum increase of the minimum distance between the currently selected experiments. Such an algorithm provides a final uniform distribution of the experiments selected from the set of allowed candidates
Marengo, E., Todeschini, R. (1992). A new algorithm for optimal, distance based, experimental design. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 16(1), 37-44 [10.1016/0169-7439(92)80076-G].
A new algorithm for optimal, distance based, experimental design
TODESCHINI, ROBERTO
1992
Abstract
A new algorithm for optimal, distance based, experimental design is presented. The proposed approach, in contrast to other optimality criteria, does not require any preliminary hypothesis about a regression model. The best set of experiments is defined through a fast exchange algorithm where, in each cycle, a substitution is selected to provide the maximum increase of the minimum distance between the currently selected experiments. Such an algorithm provides a final uniform distribution of the experiments selected from the set of allowed candidates
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