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dc.contributor.authorGilmour, S. G.-
dc.contributor.authorTrinca, L. A.-
dc.date.accessioned2014-05-20T13:47:46Z-
dc.date.accessioned2016-10-25T17:01:01Z-
dc.date.available2014-05-20T13:47:46Z-
dc.date.available2016-10-25T17:01:01Z-
dc.date.issued2000-01-01-
dc.identifierhttp://dx.doi.org/10.1080/03610920008832601-
dc.identifier.citationCommunications In Statistics-theory and Methods. New York: Marcel Dekker Inc., v. 29, n. 9-10, p. 2157-2180, 2000.-
dc.identifier.issn0361-0926-
dc.identifier.urihttp://hdl.handle.net/11449/17027-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/17027-
dc.description.abstractIt is often necessary to run response surface designs in blocks. In this paper the analysis of data from such experiments, using polynomial regression models, is discussed. The definition and estimation of pure error in blocked designs are considered. It is recommended that pure error is estimated by assuming additive block and treatment effects, as this is more consistent with designs without blocking. The recovery of inter-block information using REML analysis is discussed, although it is shown that it has very little impact if thc design is nearly orthogonally blocked. Finally prediction from blocked designs is considered and it is shown that prediction of many quantities of interest is much simpler than prediction of the response itself.en
dc.format.extent2157-2180-
dc.language.isoeng-
dc.publisherMarcel Dekker Inc-
dc.sourceWeb of Science-
dc.subjectindustrial experimentspt
dc.subjectinter-block analysispt
dc.subjectlack of fitpt
dc.subjectlinear mixed modelpt
dc.subjectpredictionpt
dc.subjectpure errorpt
dc.subjectsecond order modelpt
dc.titleSome practical advice on polynomial regression analysis from blocked response surface designsen
dc.typeoutro-
dc.contributor.institutionUniv London Queen Mary & Westfield Coll-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationUniv London Queen Mary & Westfield Coll, Sch Math Sci, London E1 4NS, England-
dc.description.affiliationUNESP, Dept Bioestat, IB, BR-18618000 Botucatu, SP, Brazil-
dc.description.affiliationUnespUNESP, Dept Bioestat, IB, BR-18618000 Botucatu, SP, Brazil-
dc.identifier.doi10.1080/03610920008832601-
dc.identifier.wosWOS:000089300900015-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofCommunications in Statistics: Theory and Methods-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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