Small area estimation combining information from several sources

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dc.contributor.author Kim, Jae Kwang
dc.contributor.author Park, Seunghwan
dc.contributor.author Kim, Jae Kwang
dc.contributor.author Kim, Seo-young
dc.contributor.department Statistics
dc.date 2018-02-18T16:53:21.000
dc.date.accessioned 2020-07-02T06:56:37Z
dc.date.available 2020-07-02T06:56:37Z
dc.date.copyright Thu Jan 01 00:00:00 UTC 2015
dc.date.issued 2015-06-01
dc.description.abstract <p>An area-level model approach to combining information from several sources is considered in the context of small area estimation. At each small area, several estimates are computed and linked through a system of structural error models. The best linear unbiased predictor of the small area parameter can be computed by the general least squares method. Parameters in the structural error models are estimated using the theory of measurement error models. Estimation of mean squared errors is also discussed. The proposed method is applied to the real problem of labor force surveys in Korea.</p>
dc.description.comments <p>This article is published as Kim, Jae-kwang, Seunghwan Park, and Seo-young Kim. "Small area estimation combining information from several sources." <em>Survey Methodology </em>41 (2015). Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/stat_las_pubs/117/
dc.identifier.articleid 1104
dc.identifier.contextkey 10455817
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_pubs/117
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/90418
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/stat_las_pubs/117/2015_Kim_SmallArea.pdf|||Fri Jan 14 18:56:19 UTC 2022
dc.subject.disciplines Applied Statistics
dc.subject.disciplines Design of Experiments and Sample Surveys
dc.subject.disciplines Probability
dc.subject.disciplines Statistical Methodology
dc.subject.keywords Area-level model
dc.subject.keywords Auxiliary information
dc.subject.keywords Measurement error models
dc.subject.keywords Structural error model
dc.subject.keywords Survey integration
dc.title Small area estimation combining information from several sources
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication fdf914ae-e48d-4f4e-bfa2-df7a755320f4
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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