Small area estimation under area-level generalized linear mixed models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F22%3A00345785" target="_blank" >RIV/68407700:21340/22:00345785 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1080/03610918.2020.1836216" target="_blank" >https://doi.org/10.1080/03610918.2020.1836216</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/03610918.2020.1836216" target="_blank" >10.1080/03610918.2020.1836216</a>
Alternative languages
Result language
angličtina
Original language name
Small area estimation under area-level generalized linear mixed models
Original language description
This paper introduces a general area-level model-based formulation to small area estimation based on generalized linear mixed models. By applying an optimization algorithm to the Laplace approximation of the likelihood, the maximum likelihood estimators of the model parameters are calculated. Empirical best predictors of small area quantities are derived and the corresponding mean squared errors are estimated by parametric bootstrap. Some simulation experiments are carried out to study the behavior of the fitting algorithm, the small area predictors and the estimators of the mean squared errors. By using data of the Spanish living condition survey of 2008, an application to the estimation of average annual net incomes in Spanish provinces by sex is given.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/EF16_019%2F0000778" target="_blank" >EF16_019/0000778: Center for advanced applied science</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Communications in Statistics - Simulation and computation
ISSN
0361-0918
e-ISSN
1532-4141
Volume of the periodical
51
Issue of the periodical within the volume
12
Country of publishing house
GB - UNITED KINGDOM
Number of pages
23
Pages from-to
7404-7426
UT code for WoS article
000582538900001
EID of the result in the Scopus database
2-s2.0-85094156915