Weighing experiments with n = 2 (mod 4) observations

Koukouvinos, C

dc.contributor.author	Koukouvinos, C	en
dc.date.accessioned	2014-03-01T01:14:16Z
dc.date.available	2014-03-01T01:14:16Z
dc.date.issued	1998	en
dc.identifier.issn	0167-9473	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/12969
dc.subject	Autocorrelation	en
dc.subject	Conference matrix	en
dc.subject	Construction	en
dc.subject	Linear model	en
dc.subject	Orthogonal design	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Statistics & Probability	en
dc.subject.other	Correlation methods	en
dc.subject.other	Functions	en
dc.subject.other	Mathematical models	en
dc.subject.other	Conference matrix	en
dc.subject.other	Linear models	en
dc.subject.other	Orthogonal designs	en
dc.subject.other	Matrix algebra	en
dc.title	Weighing experiments with n = 2 (mod 4) observations	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/S0167-9473(97)00050-9	en
heal.identifier.secondary	http://dx.doi.org/10.1016/S0167-9473(97)00050-9	en
heal.language	English	en
heal.publicationDate	1998	en
heal.abstract	In factorial experiments the use of orthogonal designs contributes decisively to the reduction of variance which is a significant factor in the improvement of industrial products. In experimental situations where n three-level factors are involved and n observations are taken, we obtain orthogonal designs from weighing matrices. In this paper we construct some new weighing matrices by constructing two sequences with elements 0, 1, -1 and zero autocorrelation function. (C) 1998 Elsevier Science B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Computational Statistics and Data Analysis	en
dc.identifier.doi	10.1016/S0167-9473(97)00050-9	en
dc.identifier.isi	ISI:000072615200003	en
dc.identifier.volume	27	en
dc.identifier.issue	1	en
dc.identifier.spage	27	en
dc.identifier.epage	31	en