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Description
  • A Fay-Herriot model having both fixed and random effects is introduced to estimate linear parameters of small areas. The model is applicable to data having a small subset of domains where direct estimates of the variable of interest cannot be described in the same way as in its complementary subset of domains. Algorithms and formulas to fit the model, to calculate EBLUPs and to estimate mean squared errors are given. A Monte Carlo simulation experiment is carried out to investigate the gain of precision obtained by using the proposed model. An application to Spanish Labour Force Survey data is also given.
  • A Fay-Herriot model having both fixed and random effects is introduced to estimate linear parameters of small areas. The model is applicable to data having a small subset of domains where direct estimates of the variable of interest cannot be described in the same way as in its complementary subset of domains. Algorithms and formulas to fit the model, to calculate EBLUPs and to estimate mean squared errors are given. A Monte Carlo simulation experiment is carried out to investigate the gain of precision obtained by using the proposed model. An application to Spanish Labour Force Survey data is also given. (en)
Title
  • An Area-Level Model with Fixed or Random Domain Effects in Small Area Estimation Problems
  • An Area-Level Model with Fixed or Random Domain Effects in Small Area Estimation Problems (en)
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  • An Area-Level Model with Fixed or Random Domain Effects in Small Area Estimation Problems
  • An Area-Level Model with Fixed or Random Domain Effects in Small Area Estimation Problems (en)
skos:notation
  • RIV/68407700:21340/11:00187457!RIV12-MSM-21340___
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  • S, Z(MSM6840770039)
http://linked.open...vai/riv/dodaniDat
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  • 185430
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  • RIV/68407700:21340/11:00187457
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  • Small area estimation; linear mixed models; Fay-Herriot regression model; fixed effects; random effects; EBLUP; Labour Force Survey (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D2C5021B5E63]
http://linked.open...i/riv/mistoVydani
  • Berlin
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  • Modern Mathematical Tools and Techniques in Capturing Complexity
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  • Esteban, M. D.
  • Herrador, M.
  • Hobza, Tomáš
  • Morales, D.
http://linked.open...n/vavai/riv/zamer
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-642-20853-9_21
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  • Springer-Verlag
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  • 978-3-642-20852-2
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  • 21340
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