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Optimum designs for estimation of regression parameters in a balanced treatment incomplete block design set-up

机译:平衡处理中不完整块设计设置中用于估计回归参数的最佳设计

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摘要

The use of covariates in block designs is necessary when the experimental errors cannot be controlled using only the qualitative factors. The choice of values of the covariates for a given set-up attaining minimum variance for estimation of the regression parameters has attracted attention in recent times. In this paper, optimum covariate designs (OCD) have been considered for the set-up of the balanced treatment incomplete block (BTIB) designs, which form an important class of test-control designs. It is seen that the OCDs depend much on the methods of construction of the basic BTIB designs. The series of BTIB designs considered in this paper are mainly those as described by Bechhofer and Tamhane (1981) and Das et al. (2005). Different combinatorial arrangements and tools such as Hadamard matrices and different kinds of products of matrices viz Khatri-Rao product and Kronecker product have been conveniently used to construct OCDs with as many covariates as possible.
机译:当不能仅使用定性因素控制实验误差时,必须在块设计中使用协变量。近来,对于给定的设置获得最小方差以估计回归参数的协变量的值的选择引起了关注。在本文中,已经考虑将最佳协变量设计(OCD)用于平衡处理不完全模块(BTIB)设计的建立,这构成了一类重要的测试控制设计。可以看出,OCD很大程度上取决于基本BTIB设计的构建方法。本文所考虑的BTIB设计系列主要是Bechhofer和Tamhane(1981)和Das等人所描述的设计。 (2005)。不同的组合安排和工具(例如Hadamard矩阵和矩阵的不同种类的产品,即Khatri-Rao乘积和Kronecker乘积)已被方便地用于构建具有尽可能多协变量的OCD。

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