D-Optimal Designs for Hierarchical Linear Models with Heteroscedastic Errors

被引:0
|
作者
Liu, Xin [1 ]
Yue, Rong-Xian [2 ]
Chatterjee, Kashinath [3 ]
机构
[1] Donghua Univ, Coll Sci, Shanghai 201620, Peoples R China
[2] Shanghai Normal Univ, Dept Math, Shanghai 200234, Peoples R China
[3] Visva Bharati Univ, Dept Stat, Santini Ketan, W Bengal, India
关键词
D-optimal design; Heteroscedasticity; Mean squared error matrix; Mixed-effect model; Equivalence theorem; Admissibility; COEFFICIENT REGRESSION-MODELS; OPTIMAL POPULATION DESIGNS; PREDICTION;
D O I
10.1007/s40304-021-00244-9
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper investigates the optimal design problem for the prediction of the individual parameters in hierarchical linear models with heteroscedastic errors. An equivalence theorem is established to characterize D-optimality of designs for the prediction based on the mean squared error matrix. The admissibility of designs is also considered and a sufficient condition to simplify the design problem is obtained. The results obtained are illustrated in terms of a simple linear model with random slope and heteroscedastic errors.
引用
收藏
页码:669 / 679
页数:11
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