MINIMAX DESIGNS IN LINEAR-REGRESSION MODELS

被引:13
|
作者
DETTE, H
HEILIGERS, B
STUDDEN, WJ
机构
[1] UNIV AUGSBURG,INST MATH,D-86159 AUGSBURG,GERMANY
[2] PURDUE UNIV,DEPT STAT,W LAFAYETTE,IN 47907
[3] UNIV GOTTINGEN,GOTTINGEN,GERMANY
来源
ANNALS OF STATISTICS | 1995年 / 23卷 / 01期
关键词
APPROXIMATE DESIGN THEORY; MINIMAX CRITERION; ELFVING SET; POLYNOMIAL REGRESSION;
D O I
10.1214/aos/1176324453
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
In the usual linear regression model we investigate the geometric structure of a class of minimax optimality criteria containing Elfving's minimax and Kiefer's phi(p)-criteria as special cases. It is shown that the optimal designs with respect to these criteria are also optimal for A'theta, where A is any inball vector (in an appropriate norm) of a generalized Elfving set. The results explain the particular role of the A- and E-optimality criterion and are applied for determining the optimal design with respect to Elfving's minimax criterion in polynomial regression up to degree 9.
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页码:30 / 40
页数:11
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