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All-Subsets Regression Under Effect Heredity Restrictions for Experimental Designs with Complex Aliasing

机译:具有遗传混叠的有效遗传约束下的全子集回归用于复杂设计的实验设计

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摘要

We consider an all-subsets regression method for models under effect heredity restrictions for experimental designs with complex aliasing, whose number of potential main effects and two-factor interactions exceed the number of runs. In this paper, we present an algorithm that systematically attempts to fit all such models. We illustrate the algorithm with two published experiments.
机译:对于具有复杂混叠的实验设计,我们考虑在模型的影响遗传限制下对模型进行全子集回归的方法,该模型的潜在主效应和两因素交互作用的数量超过了运行次数。在本文中,我们提出了一种系统地尝试拟合所有此类模型的算法。我们通过两个公开的实验来说明该算法。

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