Improved split-plot and multi-stratum designs
Improved split-plot and multi-stratum designs
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 multi-stratum, 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, i.e. 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 material is available online.
A-optimality, D-optimality, hard-to-change factor, hard-to-set factor, mixed model, prediction variance, response surface
1-20
Trinca, Luzia A.
a95c3bb6-f903-4a35-80ec-3663021270fd
Gilmour, Steven G.
984dbefa-893b-444d-9aa2-5953cd1c8b03
3 April 2015
Trinca, Luzia A.
a95c3bb6-f903-4a35-80ec-3663021270fd
Gilmour, Steven G.
984dbefa-893b-444d-9aa2-5953cd1c8b03
Abstract
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 multi-stratum, 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, i.e. 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 material is available online.
Text
MSRevisedUnblinded.pdf
- Accepted Manuscript
Available under License Other.
More information
e-pub ahead of print date: 16 May 2014
Published date: 3 April 2015
Keywords:
A-optimality, D-optimality, hard-to-change factor, hard-to-set factor, mixed model, prediction variance, response surface
Organisations:
Mathematical Sciences
Identifiers
Local EPrints ID: 367194
URI: http://eprints.soton.ac.uk/id/eprint/367194
ISSN: 0040-1706
PURE UUID: 4cb7c425-831f-45b8-bfae-e85811cc2381
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Date deposited: 23 Jul 2014 14:27
Last modified: 14 Mar 2024 17:25
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Contributors
Author:
Luzia A. Trinca
Author:
Steven G. Gilmour
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