Constructing Efficient Experimental Designs for Generalized Linear Models

被引:2
作者
Saleh, Moein [1 ]
Pan, Rong [1 ]
机构
[1] Arizona State Univ, Sch Comp Informat & Decis Syst Engn, Tempe, AZ 85281 USA
关键词
A-optimality; Coordinate Exchange Algorithm; Design of Experiments; D-optimality; I-optimality; Robust design; OPTIMUM EXPERIMENTAL-DESIGNS; LOGISTIC-REGRESSION; EXCHANGE ALGORITHMS; BINARY DATA; UNCERTAINTY; GENERATION; VARIABLES; ROBUST;
D O I
10.1080/03610918.2014.927486
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Exchange algorithms are popular for finding optimal or efficient designs for linear models, but there are few discussions of this type of algorithm for generalized linear models (GLMs) in literature. A new algorithm, generalized Coordinate Exchange Algorithm (gCEA), is developed in this article to construct efficient designs for GLMs. We compare the performance of the proposed algorithm with other optimization algorithms, including point exchange algorithm, columnwise-pairwise algorithm, simulated annealing and generic algorithm, and demonstrate the superior performance of this new algorithm.
引用
收藏
页码:2827 / 2845
页数:19
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