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A comparison of design and model selection methods for supersaturated experiments

Marley, Christopher J. and Woods, David C. (2009) A comparison of design and model selection methods for supersaturated experiments , Southampton, UK Southampton Statistical Sciences Research Institute 22pp. (S3RI Methodology Working Papers, M09/20).

Record type: Monograph (Working Paper)


Various design and model selection methods are available for supersatu-
rated designs having more factors than runs but little research is available on
their comparison and evaluation. In this paper, simulated experiments are
used to evaluate the use of E(s2)-optimal and Bayesian D-optimal designs,
and to compare three analysis strategies representing regression, shrinkage
and a novel model-averaging procedure. Suggestions are made for choosing
the values of the tuning constants for each approach. Findings include that
(i) the preferred analysis is via shrinkage; (ii) designs with similar numbers
of runs and factors can be effective for a considerable number of active effects
of only moderate size; and (iii) unbalanced designs can perform well. Some
comments are made on the performance of the design and analysis methods
when effect sparsity does not hold

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Submitted date: 4 November 2009
Organisations: Southampton Statistical Research Inst.


Local EPrints ID: 69458
PURE UUID: 47aa2d84-9406-496e-b6bb-5b44950c1809

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Date deposited: 17 Nov 2009
Last modified: 19 Jul 2017 00:12

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Author: Christopher J. Marley
Author: David C. Woods

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