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A UNIFIED APPROACH TO FACTORIAL DESIGNS WITH RANDOMIZATION RESTRICTIONS

机译:具有随机化限制的工厂设计的统一方法

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Factorial designs are commonly used to assess the impact of factors and factor combinations in industrial and agricultural experiments. Though preferred, complete randomization of trials is often infeasible, and randomization restrictions are imposed. In this paper, we discuss a finite projective geometric (PG) approach to unify the existence, construction and analysis of multistage factorial designs with randomization restrictions using randomization defining contrast subspaces (or flats of a PG). Our main focus will be on the construction of such designs, and developing a word length pattern scheme that can be used for generalizing the traditional design ranking criteria for factorial designs. We also present a novel isomorphism check algorithm for these designs.
机译:因子设计通常用于评估因子和因子组合在工业和农​​业实验中的影响。尽管比较可取,但是完全不可能进行试验的完全随机化,并且施加了随机限制。在本文中,我们讨论了一种有限投影几何(PG)方法,该方法通过使用定义对比子空间(或PG的平面)的随机化来统一具有随机化限制的多级因子设计的存在,构造和分析。我们的主要重点将放在此类设计的构建上,并开发一种字长模式方案,该方案可用于泛化析因设计的传统设计排名标准。我们还为这些设计提出了一种新颖的同构检查算法。

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