Improved Split-Plot and Multistratum Designs

被引:21
|
作者
Trinca, Luzia A. [1 ]
Gilmour, Steven G. [2 ]
机构
[1] Sao Paulo State Univ, Dept Biostat, Botucatu, SP, Brazil
[2] Univ Southampton, Southampton Stat Sci Res Inst, Southampton SO17 1BJ, Hants, England
基金
巴西圣保罗研究基金会; 英国工程与自然科学研究理事会;
关键词
Response surface; Hard-to-change factor; D-optimality; Prediction variance; Mixed model; Hard-to-set factor; A-optimality; RESPONSE-SURFACE DESIGNS; FACTORIAL; CONSTRUCTION; ALGORITHM;
D O I
10.1080/00401706.2014.915235
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
Many industrial experiments involve some factors whose levels are harder to set than others. The best way to deal with these is to plan the experiment carefully as a split-plot, or more generally a multistratum, design. Several different approaches for constructing split-plot type response surface designs have been proposed in the literature since 2001, which has allowed experimenters to make better use of their resources by using more efficient designs than the classical balanced ones. One of these approaches, the stratum-by-stratum strategy has been shown to produce designs that are less efficient than locally D-optimal designs. An improved stratum-by-stratum algorithm is given, which, though more computationally intensive than the old one, makes better use of the advantages of this approach, that is, it can be used for any structure and does not depend on prior estimates of the variance components. This is shown to be almost as good as the locally optimal designs in terms of their own criteria and more robust across a range of criteria. Supplementary materials for this article are available online.
引用
收藏
页码:145 / 154
页数:10
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