最优判别设计
Optimal discrimination designs
摘要：
我们考虑竞争回归模型之间的模型判别构造最优设计的问题。各种新的性质的最优设计相对于流行的$T$ -最优性准则推导出来，这在许多情况下允许明确确定的$T$ -最优设计。它也表明，在嵌套线性模型的支持点的数量$T$ -最优设计通常是太小，估计所有参数的扩展模型。在许多情况下，$T$ -最优设计通常不是唯一的，在这种情况下，我们给出了所有$T$ -最优设计的一个特征。最后，通过一个小型的模拟研究，$T$ -最优设计与最优判别设计进行了比较。
英文摘要：
We consider the problem of constructing optimal designs for model discrimination between competing regression models. Various new properties of optimal designs with respect to the popular $T$-optimality criterion are derived, which in many circumstances allow an explicit determination of $T$-optimal designs. It is also demonstrated, that in nested linear models the number of support points of $T$-optimal designs is usually too small to estimate all parameters in the extended model. In many cases $T$-optimal designs are usually not unique, and in this situation we give a characterization of all $T$-optimal designs. Finally, $T$-optimal designs are compared with optimal discriminating designs with respect to alternative criteria by means of a small simulation study.
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