Small area estimation combining information from several sources

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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
Publisher
STATISTICS CANADA
Issue Date
2015-06
Language
English
Article Type
Article
Keywords

ERROR; MODEL; PREDICTION; BIAS

Citation

SURVEY METHODOLOGY, v.41, no.1, pp.21 - 36

ISSN
0714-0045
URI
http://hdl.handle.net/10203/212989
Appears in Collection
MA-Journal Papers(저널논문)
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