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DC Field | Value | Language |
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dc.contributor.author | Franco, Bruno Chaves | - |
dc.contributor.author | Castagliola, Philippe | - |
dc.contributor.author | Celano, Giovanni | - |
dc.contributor.author | Branco Costa, Antonio Fernando | - |
dc.date.accessioned | 2014-12-03T13:11:49Z | - |
dc.date.accessioned | 2016-10-25T20:15:17Z | - |
dc.date.available | 2014-12-03T13:11:49Z | - |
dc.date.available | 2016-10-25T20:15:17Z | - |
dc.date.issued | 2014-07-03 | - |
dc.identifier | http://www.tandfonline.com/doi/abs/10.1080/02664763.2013.871507 | - |
dc.identifier.citation | Journal of Applied Statistics. Abingdon: Taylor & Francis Ltd, v. 41, n. 7, p. 1408-1421, 2014. | - |
dc.identifier.issn | 0266-4763 | - |
dc.identifier.uri | http://hdl.handle.net/11449/113605 | - |
dc.identifier.uri | http://acervodigital.unesp.br/handle/11449/113605 | - |
dc.description.abstract | The 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.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | - |
dc.format.extent | 1408-1421 | - |
dc.language.iso | eng | - |
dc.publisher | Taylor & Francis Ltd | - |
dc.source | Web of Science | - |
dc.subject | inclusion probability | en |
dc.subject | auxiliary information | en |
dc.subject | variance | en |
dc.subject | low income proportion | en |
dc.subject | quantile | en |
dc.title | A new sampling strategy to reduce the effect of autocorrelation on a control chart | en |
dc.type | outro | - |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | - |
dc.contributor.institution | LUNAM Univ | - |
dc.contributor.institution | Univ Nantes | - |
dc.contributor.institution | IRCCyN UMR CNRS 6597 | - |
dc.contributor.institution | Univ Catania | - |
dc.description.affiliation | Sao Paulo State Univ, Prod Dept, Guaratingueta, SP, Brazil | - |
dc.description.affiliation | LUNAM Univ, IRCCyN UMR CNRS 6597, Nantes, France | - |
dc.description.affiliation | Univ Nantes, LUNAM Univ, Nantes, France | - |
dc.description.affiliation | IRCCyN UMR CNRS 6597, Nantes, France | - |
dc.description.affiliation | Univ Catania, Dept Ind Engn, Catania, Italy | - |
dc.description.affiliationUnesp | Sao Paulo State Univ, Prod Dept, Guaratingueta, SP, Brazil | - |
dc.identifier.wos | WOS:000335854800002 | - |
dc.rights.accessRights | Acesso restrito | - |
dc.relation.ispartof | Journal of Applied Statistics | - |
Appears in Collections: | Artigos, TCCs, Teses e Dissertações da Unesp |
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