A Bayesian design criterion for locating the optimum point on a response surface

被引：5

作者：

Gilmour, SG

Mead, R

机构：

[1] Univ London, Queen Mary, Sch Math Sci, London E1 4NS, England

[2] Univ Reading, Sch Appl Stat, Reading RG6 6FN, Berks, England

来源：

STATISTICS & PROBABILITY LETTERS | 2003年 / 64卷 / 03期

关键词：

A(B)-optimality; industrial experimentation; response surface methods; sequential design;

D O I：

10.1016/S0167-7152(03)00154-8

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：

Most factorial experiments in industrial research form one stage in a sequence of experiments and so considerable prior knowledge is often available from earlier stages. A Bayesian A-optimality criterion is proposed for choosing designs, when each stage in experimentation consists of a small number of runs and the objective is to optimise a response. Simple formulae for the weights are developed, some examples of the use of the design criterion are given and general recommendations are made. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：235 / 242

页数：8