Screening designs for model selection
Screening designs for model selection
复制标题
模型选择的筛选设计
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
William Li
中科院分区：
文献类型：
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作者：
William Li
在所有因素都有两个水平的情况下，讨论了从一组感兴趣的模型中选择一个好模型的实验设计问题。所考虑的模型涉及主效应和一些双因子相互作用。介绍了模型筛选设计选择的两个准则。一个标准选择允许估计最大数量的不同模型的设计（估计能力）。另一个是最大限度地提高设计区分竞争模型的能力（模型区分）。针对这些标准构建了12次、16次和20次运行的最佳两水平正交设计并制成表格以供实际使用。此外，还讨论了构造非正交设计的几种方法。本章包括正交设计的新成果，是有效的模式歧视。
The problem of designing an experiment for selecting a good model from a set of models of interest is discussed in the setting where all factors have two levels. The models considered involve main effects and a few two-factor interactions. Two criteria for the selection of designs for model screening are introduced. One criterion selects designs that allow the maximum number of distinct models to be estimated (estimation capacity). The other maximizes the capability of the design to discriminate among competing models (model discrimination). Two-level orthogonal designs for 12, 16, and 20 runs that are optimal with respect to these criteria are constructed and tabulated for practical use. In addition, several approaches are discussed for the construction of nonorthogonal designs. The chapter includes new results on orthogonal designs that are effective for model discrimination.