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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/113605
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dc.contributor.authorFranco, Bruno Chaves-
dc.contributor.authorCastagliola, Philippe-
dc.contributor.authorCelano, Giovanni-
dc.contributor.authorBranco Costa, Antonio Fernando-
dc.date.accessioned2014-12-03T13:11:49Z-
dc.date.accessioned2016-10-25T20:15:17Z-
dc.date.available2014-12-03T13:11:49Z-
dc.date.available2016-10-25T20:15:17Z-
dc.date.issued2014-07-03-
dc.identifierhttp://www.tandfonline.com/doi/abs/10.1080/02664763.2013.871507-
dc.identifier.citationJournal of Applied Statistics. Abingdon: Taylor & Francis Ltd, v. 41, n. 7, p. 1408-1421, 2014.-
dc.identifier.issn0266-4763-
dc.identifier.urihttp://hdl.handle.net/11449/113605-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/113605-
dc.description.abstractThe ratio method is commonly used to the estimation of means and totals. This method was extended to the problem of estimating the distribution function. An alternative ratio estimator of the distribution function is defined. A result that compares the variances of the aforementioned ratio estimators is used to define optimum design-based ratio estimators of the distribution function. Different empirical results indicate that the optimum ratio estimators can be more efficient than alternative ratio estimators. In addition, we show by simulations that alternative ratio estimators can have large biases, whereas biases of the optimum ratio estimators are negligible in this situation.en
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
dc.format.extent1408-1421-
dc.language.isoeng-
dc.publisherTaylor & Francis Ltd-
dc.sourceWeb of Science-
dc.subjectinclusion probabilityen
dc.subjectauxiliary informationen
dc.subjectvarianceen
dc.subjectlow income proportionen
dc.subjectquantileen
dc.titleA new sampling strategy to reduce the effect of autocorrelation on a control charten
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionLUNAM Univ-
dc.contributor.institutionUniv Nantes-
dc.contributor.institutionIRCCyN UMR CNRS 6597-
dc.contributor.institutionUniv Catania-
dc.description.affiliationSao Paulo State Univ, Prod Dept, Guaratingueta, SP, Brazil-
dc.description.affiliationLUNAM Univ, IRCCyN UMR CNRS 6597, Nantes, France-
dc.description.affiliationUniv Nantes, LUNAM Univ, Nantes, France-
dc.description.affiliationIRCCyN UMR CNRS 6597, Nantes, France-
dc.description.affiliationUniv Catania, Dept Ind Engn, Catania, Italy-
dc.description.affiliationUnespSao Paulo State Univ, Prod Dept, Guaratingueta, SP, Brazil-
dc.identifier.wosWOS:000335854800002-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofJournal of Applied Statistics-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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