Model identification using 27 runs three level orthogonal arrays

Angelopoulos, P; Evangelaras, H; Koukouvinos, C

dc.contributor.author	Angelopoulos, P	en
dc.contributor.author	Evangelaras, H	en
dc.contributor.author	Koukouvinos, C	en
dc.date.accessioned	2014-03-01T01:31:07Z
dc.date.available	2014-03-01T01:31:07Z
dc.date.issued	2009	en
dc.identifier.issn	0266-4763	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19748
dc.subject	Geometric isomorphism	en
dc.subject	Hidden projection properties	en
dc.subject	Orthogonal arrays	en
dc.subject	Quantitative factors	en
dc.subject.classification	Statistics & Probability	en
dc.subject.other	FACTORIAL-DESIGNS	en
dc.title	Model identification using 27 runs three level orthogonal arrays	en
heal.type	journalArticle	en
heal.identifier.primary	10.1080/02664760802382509	en
heal.identifier.secondary	http://dx.doi.org/10.1080/02664760802382509	en
heal.language	English	en
heal.publicationDate	2009	en
heal.abstract	In this paper we examine all the combinatorial non-isomorphic OA(27, q, 3, t), with 3≤q≤13 three level quantitative factors, with respect to model identification, estimation capacity and efficiency. We use the popular D-efficiency criterion to evaluate the ability of each design considered in estimating the parameters of a second-order model with adequate efficiency. The prior selection of the 'middle' level of factors plays an important role in the results.	en
heal.publisher	ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD	en
heal.journalName	Journal of Applied Statistics	en
dc.identifier.doi	10.1080/02664760802382509	en
dc.identifier.isi	ISI:000260573200004	en
dc.identifier.volume	36	en
dc.identifier.issue	1	en
dc.identifier.spage	33	en
dc.identifier.epage	38	en