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Small area estimation of proportions under area-level compositional mixed models
dc.contributor.author | Dolores Esteban, María | |
dc.contributor.author | Lombardía, María José | |
dc.contributor.author | López Vizcaíno, María Esther | |
dc.contributor.author | Morales, Domingo | |
dc.contributor.author | Pérez, Agustín | |
dc.date.accessioned | 2023-12-11T09:15:39Z | |
dc.date.available | 2023-12-11T09:15:39Z | |
dc.date.issued | 2020-09 | |
dc.identifier.citation | Esteban, M.D., Lombardía, M.J., López-Vizcaíno, E. et al. Small area estimation of proportions under area-level compositional mixed models. TEST 29, 793–818 (2020). https://doi.org/10.1007/s11749-019-00688-w | es_ES |
dc.identifier.issn | 1863-8260 | |
dc.identifier.uri | http://hdl.handle.net/2183/34438 | |
dc.description.abstract | [Abstract]: This paper introduces area-level compositional mixed models by applying transformations to a multivariate Fay–Herriot model. Small area estimators of the proportions of the categories of a classification variable are derived from the new model, and the corresponding mean squared errors are estimated by parametric bootstrap. Several simulation experiments designed to analyse the behaviour of the introduced estimators are carried out. An application to real data from the Spanish Labour Force Survey of Galicia (north-west of Spain), in the first quarter of 2017, is given. The target is the estimation of domain proportions of people in the four categories of the variable labour status: under 16 years, employed, unemployed and inactive. | es_ES |
dc.description.sponsorship | Supported by the Instituto Galego de Estatística, by the grants PGC2018-096840-B-I00 and MTM2017-82724-R of the Spanish Ministerio de Economía y Competitividad and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2016-015 and Centro Singular de Investigación de Galicia ED431G/01), all of them through the ERDF. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C-2016-015 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G/01 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Springer Nature | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096840-B-I00/ES/MODELOS MIXTOS Y ESTIMACION EN AREAS PEQUEÑAS | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/MTM2017-82724-R/ES/INFERENCIA ESTADISTICA FLEXIBLE PARA DATOS COMPLEJOS DE GRAN VOLUMEN Y DE ALTA DIMENSION | es_ES |
dc.relation.uri | https://doi.org/10.1007/s11749-019-00688-w | es_ES |
dc.rights | Atribución 3.0 España | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Labour Force Survey | es_ES |
dc.subject | Small area estimation | es_ES |
dc.subject | Area-level models | es_ES |
dc.subject | Compositional data | es_ES |
dc.subject | Bootstrap | es_ES |
dc.subject | Labour status | es_ES |
dc.title | Small area estimation of proportions under area-level compositional mixed models | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | TEST | es_ES |
UDC.volume | 29 | es_ES |
UDC.startPage | 793 | es_ES |
UDC.endPage | 818 | es_ES |
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