Efficient maximin distance designs for experiments in mixtures

Coetzer R.L.J. ; Rossouw R.F. ; Le Roux N.J. (2012)


In this paper, different dissimilarity measures are investigated to construct maximin designs for compositional data. Specifically, the effect of different dissimilarity measures on the maximin design criterion for two case studies is presented. Design evaluation criteria are proposed to distinguish between the maximin designs generated. An optimization algorithm is also presented. Divergence is found to be the best dissimilarity measure to use in combination with the maximin design criterion for creating space-filling designs for mixture variables. © 2012 Copyright Taylor and Francis Group, LLC.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/49247
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