共 4 条
Some practical advice on polynomial regression analysis from blocked response surface designs
被引:23
|作者:
Gilmour, SG
Trinca, LA
机构:
[1] Univ London Queen Mary & Westfield Coll, Sch Math Sci, London E1 4NS, England
[2] UNESP, Dept Bioestat, IB, BR-18618000 Botucatu, SP, Brazil
关键词:
industrial experiments;
inter-block analysis;
lack of fit;
linear mixed model;
prediction;
pure error;
second order model;
D O I:
10.1080/03610920008832601
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:
It is often necessary to run response surface designs in blocks. In this paper the analysis of data from such experiments, using polynomial regression models, is discussed. The definition and estimation of pure error in blocked designs are considered. It is recommended that pure error is estimated by assuming additive block and treatment effects, as this is more consistent with designs without blocking. The recovery of inter-block information using REML analysis is discussed, although it is shown that it has very little impact if thc design is nearly orthogonally blocked. Finally prediction from blocked designs is considered and it is shown that prediction of many quantities of interest is much simpler than prediction of the response itself.
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页码:2157 / 2180
页数:24
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