论文标题
通用线性模型中最佳设计的内在和均衡性：伽马模型
In- and Equivariance for Optimal Designs in Generalized Linear Models: The Gamma Model
论文作者
论文摘要
我们概述了对均值和不变性在设计广义线性模型设计中的有用性。与线性模型相反，必须考虑在实验设置和线性组件中的位置参数上同时起作用的成对转换。鉴于实验设置的转换，参数转换不是唯一的，并且可能是非线性的，以进一步使用模型结构。一般概念和结果通过具有伽马分布响应的模型来说明。对于常见的D-和IMSE标准，获得了局部最佳和最大效率设计。
We give an overview over the usefulness of the concept of equivariance and invariance in the design of experiments for generalized linear models. In contrast to linear models here pairs of transformations have to be considered which act simultaneously on the experimental settings and on the location parameters in the linear component. Given the transformation of the experimental settings the parameter transformations are not unique and may be nonlinear to make further use of the model structure. The general concepts and results are illustrated by models with gamma distributed response. Locally optimal and maximin efficient design are obtained for the common D- and IMSE-criterion.
