MODEL-ROBUST D- AND A-OPTIMAL DESIGNS FOR MIXTURE EXPERIMENTS

被引：0

作者：

Lo Huang, Mong-Na ^{[1
]}

Hsu, Hsiang-Ling ^{[1
]}

Chou, Chao-Jin ^{[1
]}

Klein, Thomas ^{[2
]}

机构：

[1] Natl Sun Yat Sen Univ, Dept Appl Math, Kaohsiung 804, Taiwan

[2] Tech Univ Munich, Zentrum Math, D-85748 Garching, Germany

来源：

STATISTICA SINICA | 2009年 / 19卷 / 03期

关键词：

centroid design; complete class; design efficiency; design optimality; exchangeability; Kiefer ordering; polynomial regression; robustness; POLYNOMIAL REGRESSION; SIMPLEX-DESIGNS;

D O I：

暂无

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：

This paper investigates optimal designs for mixture experiments when there is uncertainty as to whether a polynomial regression model of degree one or two is appropriate. Three groups of novel results are presented: (i) a complete class of designs relative to certain mixed design criteria, (ii) model-robust D- and A-optimal designs, (iii) D- and A-optimal designs with maximin efficiencies under variation of the design criterion.

引用

页码：1055 / 1075

页数：21

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