Robust designs for approximately polynomial regression

被引:13
|
作者
Liu, SX
Wiens, DP
机构
[1] Mt Royal Coll, Dept Engn Math & Phys, Calgary, AB T3E 6K6, Canada
[2] Univ Alberta, Dept Math Sci, Edmonton, AB T6G 2G1, Canada
关键词
bounded bias; bounded variance; approximate polynomial regression; minimax designs;
D O I
10.1016/S0378-3758(97)00039-6
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
We study designs for the regression model E[Y\x]=Sigma(j=0)(p-1)theta(j)x(j)+x(p) psi(x), where psi(x) is unknown but bounded in absolute value by a given function phi(x). This class of response functions models departures from an exact polynomial response. We consider the construction of designs which are robust, with respect to various criteria, as the true response varies over this class. The resulting designs are shown to compare favourably with others in the literature. (C) 1997 Elsevier Science B.V.
引用
收藏
页码:369 / 381
页数:13
相关论文
共 50 条