Construction of optimal multi-level supersaturated designs

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dc.creatorXu, Hongquan
dc.creatorWu, C. F. J.
dc.date2006-03-03
dc.date.accessioned2026-07-07T08:07:38Z
dc.date.available2026-07-07T08:07:38Z
dc.descriptionA supersaturated design is a design whose run size is not large enough for estimating all the main effects. The goodness of multi-level supersaturated designs can be judged by the generalized minimum aberration criterion proposed by Xu and Wu [Ann. Statist. 29 (2001) 1066--1077]. A new lower bound is derived and general construction methods are proposed for multi-level supersaturated designs. Inspired by the Addelman--Kempthorne construction of orthogonal arrays, several classes of optimal multi-level supersaturated designs are given in explicit form: Columns are labeled with linear or quadratic polynomials and rows are points over a finite field. Additive characters are used to study the properties of resulting designs. Some small optimal supersaturated designs of 3, 4 and 5 levels are listed with their properties.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053605000000688 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0603079
dc.identifierhttp://arxiv.org/abs/math/0603079
dc.identifierAnnals of Statistics 2005, Vol. 33, No. 6, 2811-2836
dc.identifierdoi:10.1214/009053605000000688
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130995
dc.subjectStatistics Theory
dc.subject62K15 (Primary) 62K05, 05B15 (Secondary)
dc.titleConstruction of optimal multi-level supersaturated designs
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