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Small area estimation using reduced rank regression models
Stockholm University, Faculty of Social Sciences, Department of Statistics.ORCID iD: 0000-0002-8610-0365
2019 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415XArticle in journal (Refereed) Epub ahead of print
Abstract [en]

Small area estimation techniques have got a lot of attention during the last decades due to their important applications in survey studies. Mixed linear models and reduced rank regression analysis are jointly used when considering small area estimation. Estimates of parameters are presented as well as prediction of random effects and unobserved area measurements.

Place, publisher, year, edition, pages
2019.
Keywords [en]
Growth curve model, mixed linear model, reduced rank regression
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:su:diva-168262DOI: 10.1080/03610926.2019.1586946ISI: 000469651700001OAI: oai:DiVA.org:su-168262DiVA, id: diva2:1307560
Funder
Swedish Research Council, 2017-03003Riksbankens Jubileumsfond, P14-0641:1Available from: 2019-04-28 Created: 2019-04-28 Last updated: 2019-10-18

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