Further contributions to nonisomorphic two level orthogonal arrays

Evangelaras, H; Koukouvinos, C; Lappas, E

dc.contributor.author	Evangelaras, H	en
dc.contributor.author	Koukouvinos, C	en
dc.contributor.author	Lappas, E	en
dc.date.accessioned	2014-03-01T01:26:23Z
dc.date.available	2014-03-01T01:26:23Z
dc.date.issued	2007	en
dc.identifier.issn	0378-3758	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18051
dc.subject	Construction algorithm	en
dc.subject	Estimation capacity	en
dc.subject	Isomorphism	en
dc.subject	Minimum aberration	en
dc.subject	Orthogonal arrays	en
dc.subject.classification	Statistics & Probability	en
dc.subject.other	HADAMARD-MATRICES	en
dc.subject.other	INEQUIVALENT PROJECTIONS	en
dc.subject.other	ABERRATION	en
dc.subject.other	DESIGNS	en
dc.title	Further contributions to nonisomorphic two level orthogonal arrays	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.jspi.2006.03.006	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.jspi.2006.03.006	en
heal.language	English	en
heal.publicationDate	2007	en
heal.abstract	In this paper we construct all possible orthogonal arrays OA(n. q, 2, t) with 12 <= n <= 24 runs and 3 <= q <= 6 factors, with 28 <= n <= 40 runs and 3 <= q <= 5 factors as well as those with 44 <= n <= 64 runs and 3 <= q <= 4 factors and present those that are nonisomorphic. A discussion on the novelty and the superiority of many of the designs found in terms of isomorphism, generalized minimum aberration and estimation capacity has also been made. (c) 2006 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	Journal of Statistical Planning and Inference	en
dc.identifier.doi	10.1016/j.jspi.2006.03.006	en
dc.identifier.isi	ISI:000245168100029	en
dc.identifier.volume	137	en
dc.identifier.issue	6	en
dc.identifier.spage	2080	en
dc.identifier.epage	2086	en