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dc.contributor.authorDolores Esteban, María
dc.contributor.authorLombardía, María José
dc.contributor.authorLópez Vizcaíno, María Esther
dc.contributor.authorMorales, Domingo
dc.contributor.authorPérez, Agustín
dc.date.accessioned2022-12-30T11:37:35Z
dc.date.available2022-12-30T11:37:35Z
dc.date.issued2022
dc.identifier.citationM. D. Esteban, M. J. Lombardía, E. López-Vizcaíno, D. Morales, and A. Pérez, “Empirical best prediction of small area bivariate parameters,” Scandinavian Journal of Statistics, vol. 49, no. 4, pp. 1699–1727, 2022, doi: 10.1111/sjos.12618.es_ES
dc.identifier.issn0303-6898
dc.identifier.issn1467-9469
dc.identifier.urihttp://hdl.handle.net/2183/32261
dc.description.abstract[Abstract]: This paper introduces empirical best predictors of small area bivariate parameters, like ratios of sums or sums of ratios, by assuming that the target unit-level vector follows a bivariate nested error regression model. The corresponding means squared errors are estimated by parametric bootstrap. Several simulation experiments empirically study the behavior of the introduced statistical methodology. An application to real data from the Spanish household budget survey gives estimators of ratios of food household expenditures by provinces.es_ES
dc.description.sponsorshipGeneralitat Valenciana; Prometeo/2021/063es_ES
dc.description.sponsorshipMinisterio de Ciencia e Innovación; PGC2018-096840- B-I00es_ES
dc.description.sponsorshipMinisterio de Ciencia e Innovación; PID2020- 113578RB-I00es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2020/14es_ES
dc.description.sponsorshipXunta de Galicia; COV20/00604es_ES
dc.language.isoenges_ES
dc.publisherWiley-Blackwell Publishing Ltdes_ES
dc.relation.urihttps://doi.org/10.1111/sjos.12618es_ES
dc.rightsAtribución-NoComercial 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/es/*
dc.subjectbest linear unbiased predictorses_ES
dc.subjecthousehold budget surveyses_ES
dc.subjectmultivariate linear mixed modelses_ES
dc.subjectnested error regression modelses_ES
dc.subjectratio estimatorses_ES
dc.subjectsmall area estimationes_ES
dc.titleEmpirical best prediction of small area bivariate parameterses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleScandinavian Journal of Statisticses_ES
UDC.volume49es_ES
UDC.issue4es_ES
UDC.startPage1699es_ES
UDC.endPage1727es_ES


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