Factor Screening via Supersaturated Designs

Steven G. Gilmour ()
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Steven G. Gilmour: University of London, School of Mathematical Sciences, Queen Mary

Chapter 8 in Screening, 2006, pp 169-190 from Springer

Abstract: Abstract Supersaturated designs are fractional factorial designs that have too few runs to allow the estimation of the main effects of all the factors in the experiment. There has been a great deal of interest in the development of these designs for factor screening in recent years. A review of this work is presented, including criteria for design selection, in particular the popular E(s 2) criterion, and methods for constructing supersaturated designs, both combinatorial and computational. Various methods, both classical and partially Bayesian, have been suggested for the analysis of data from supersaturated designs and these are critically reviewed and illustrated. Recommendations are made about the use of supersaturated designs in practice and suggestions for future research are given.

Keywords: Optimal Design; Fractional Factorial Design; Hadamard Matrice; Hadamard Matrix; Balance Incomplete Block Design (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-0-387-28014-1_8

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DOI: 10.1007/0-387-28014-6_8

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