Model-robust R-optimal designs in linear regression models

被引：3

作者：

Liu, Xin ^{[1
]}

Yue, Rong-Xian ^{[2
,3
]}

Chatterjee, Kashinath ^{[4
]}

机构：

[1] Donghua Univ, Coll Sci, Shanghai 201600, Peoples R China

[2] Shanghai Normal Univ, Coll Math & Sci, Shanghai 200234, Peoples R China

[3] Sci Comp Key Lab Shanghai Univ, Shanghai 200234, Peoples R China

[4] Visva Bharati Univ, Dept Stat, Santini Ketan, W Bengal, India

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2015年 / 167卷

关键词：

R-optimality; Robust designs; Elfving's theorem; General equivalence theorem; TRIGONOMETRIC REGRESSION; ELFVINGS THEOREM;

D O I：

10.1016/j.jspi.2015.05.003

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 considers an extension of R-optimality to model-robust optimal design, where a prior probability is set on a class of candidate linear models. A generalization of Elfving's theorem is proved, which gives a geometrical characterization of model-robust R-optimal designs. An equivalence theorem is presented and used to check optimality of designs in a few illustrative examples. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：135 / 143

页数：9

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