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dc.contributor.authorCosta, Àlex
dc.contributor.authorSatorra, A.
dc.contributor.authorVentura, Eva
dc.date.accessioned2007-11-12T18:58:15Z
dc.date.available2007-11-12T18:58:15Z
dc.date.issued2004
dc.identifier.citationCosta, Àlex; Satorra, A.; Ventura, Eva. "Improving both domain and total area estimation by composition". SORT, 2004, Vol. 28, núm. 1
dc.identifier.issn1696-2281
dc.identifier.urihttp://hdl.handle.net/2099/3741
dc.description.abstractIn this article we propose small area estimators for both the small and large area parameters. When the objective is to estimate parameters at both levels, optimality is achieved by a sample design that combines fixed and proportional allocation. In such a design, one fraction of the sample is distributed proportionally among the small areas and the rest is evenly distributed. Simulation is used to assess the performance of the direct estimator and two composite small area estimators, for a range of sample sizes and different sample distributions. Performance is measured in terms of mean squared errors for both small and large area parameters. Small area composite estimators open the possibility of reducing the sample size when the desired precision is given, or improving precision for a given sample size.
dc.format.extent69-86
dc.language.isoeng
dc.publisherInstitut d'Estadística de Catalunya
dc.relation.ispartofSORT. 2004, Vol. 28, Núm. 1 [January-June]
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/es/
dc.subject.otherInference
dc.subject.otherMultivariate analysis
dc.titleImproving both domain and total area estimation by composition
dc.typeArticle
dc.subject.lemacInferència
dc.subject.lemacAnàlisi multivariable
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::62 Statistics::62J Linear inference, regression
dc.subject.amsClassificació AMS::62 Statistics::62H Multivariate analysis
dc.rights.accessOpen Access
local.personalitzacitaciotrue


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