Some robust design strategies for percentile estimation in binary response models

被引:20
作者
Biedermann, Stefanie [1 ]
Dette, Holger
Pepelyshev, Andrey
机构
[1] Univ Southampton, Sch Math, Highfield SO17 1BJ, England
[2] Ruhr Univ Bochum, Dept Math, DE-44780 Bochum, Germany
[3] St Petersburg State Univ, Dept Math, St Petersburg 198904, Russia
来源
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 2006年 / 34卷 / 04期
关键词
binary response model; c-efficiency; multiobjective design; optimal design; percentile estimation; robustness;
D O I
10.1002/cjs.5550340404
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
For the problem of percentile estimation of a quantal response curve, the authors determine multiobjective designs which are robust with respect to misspecifications of the model assumptions. They propose a maximin approach based on efficiencies which leads to designs that are simultaneously efficient with respect to various choices of link functions and parameter regions. Furthermore, the authors deal with the problems of designing model and percentile robust experiments. They give various examples of such designs, which are calculated numerically.
引用
收藏
页码:603 / 622
页数:20
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