规模和费用同时受约束的近似D-最优试验设计
Approximate D-optimal Experimental Design with Simultaneous Size and Cost Constraints
摘要：
考虑一个实验，它有一组有限的设计点，代表允许的试验条件。假设每个试验都与取决于所选设计点的成本相关联。本文研究了同时限制规模和总费用的近似D-最优试验设计的构造问题。对于尺寸和成本约束的D-最优性问题，我们制定了一个等价定理和规则的冗余设计点的删除。我们还提出了一个简单的单调收敛的“重心”算法，使我们能够数值计算的大小和成本约束的近似D-最优设计。
英文摘要：
Consider an experiment with a finite set of design points representing permissible trial conditions. Suppose that each trial is associated with a cost that depends on the selected design point. In this paper, we study the problem of constructing an approximate D-optimal experimental design with simultaneous restrictions on the size and on the total cost. For the problem of size-and-cost constrained D-optimality, we formulate an equivalence theorem and rules for the removal of redundant design points. We also propose a simple monotonically convergent "barycentric" algorithm that allows us to numerically compute a size-and-cost constrained approximate D-optimal design.
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