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Consider an experiment with a finite set of design points representingpermissible trial conditions. Suppose that each trial is associated with a costthat depends on the selected design point. In this paper, we study the problemof constructing an approximate D-optimal experimental design with simultaneousrestrictions on the size and on the total cost. For the problem ofsize-and-cost constrained D-optimality, we formulate an equivalence theorem andrules for the removal of redundant design points. We also propose a simplemonotonically convergent "barycentric" algorithm that allows us to numericallycompute a size-and-cost constrained approximate D-optimal design.

Approximate D-optimal Experimental Design with Simultaneous Size and Cost Constraints