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Utilize este identificador para citar ou criar um link para este item: http://acervodigital.unesp.br/handle/11449/16955
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dc.contributor.authorTrinca, L. A.-
dc.contributor.authorGilmour, S. G.-
dc.date.accessioned2014-05-20T13:47:38Z-
dc.date.accessioned2016-10-25T17:00:57Z-
dc.date.available2014-05-20T13:47:38Z-
dc.date.available2016-10-25T17:00:57Z-
dc.date.issued2001-02-01-
dc.identifierhttp://dx.doi.org/10.1198/00401700152404291-
dc.identifier.citationTechnometrics. Alexandria: Amer Statistical Assoc, v. 43, n. 1, p. 25-33, 2001.-
dc.identifier.issn0040-1706-
dc.identifier.urihttp://hdl.handle.net/11449/16955-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/16955-
dc.description.abstractResponse surface designs are usually described as if the treatments have been completely randomized to the experimental units. However, in practice there is often a structure to the units, implying the need for blocking. If, in addition, some factors are more difficult to vary between units than others, a multistratum structure arises naturally. We present a general strategy for constructing response surface designs in multistratum unit structures. Designs are constructed stratum by stratum, starting in the highest stratum. In each stratum a prespecified treatment set for the factors applied in that stratum is arranged to be nearly orthogonal to the units in the higher strata, allowing-for all the effects that have to be estimated. Three examples are given to show the applicability of the method and are also used to check the relationship of the final design to the choice of treatment set. Finally, some practical considerations in randomization are discussed.en
dc.format.extent25-33-
dc.language.isoeng-
dc.publisherAmer Statistical Assoc-
dc.sourceWeb of Science-
dc.subjectblock structurept
dc.subjectfactorial designpt
dc.subjectindustrial experimentationpt
dc.subjectinterchange algorithmpt
dc.subjectresidual maximum likelihood (REML)pt
dc.subjectsplit-plot designpt
dc.titleMultistratum response surface designsen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniv London-
dc.description.affiliationUNESP, Dept Bioestatist, IB, BR-18618000 Botucatu, SP, Brazil-
dc.description.affiliationUniv London, Sch Math Sci, London E1 4NS, England-
dc.description.affiliationUnespUNESP, Dept Bioestatist, IB, BR-18618000 Botucatu, SP, Brazil-
dc.identifier.doi10.1198/00401700152404291-
dc.identifier.wosWOS:000167840800003-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofTechnometrics-
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