Application of mixed logistic model in small area estimation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F14%3A00222919" target="_blank" >RIV/68407700:21340/14:00222919 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Application of mixed logistic model in small area estimation
Original language description
Small area estimation (SAE) is in need of reliable methods for statistical inference. Direct estimation from particular small areas might not be feasible and models that borrow strength from other areas are used. For binary data, a logistic model is oneof the most used in practice. In this work, the logistic mixed model is introduced. Then, parameter estimation techniques based on Laplace approximation of likelihood are outlined. The pseudo empirical best linear unbiased predictors (pseudo?EBLUP) of area parameters are derived. The random area effects logistic model is compared to a logistic model with area effects treated as fixed in a set of Monte Carlo simulations. Performance of both models is discussed. Finally, the results are compared to the corresponding results of a Fay?Herriot model.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of Stochastic and Physical Monitoring Systems 2014
ISBN
978-80-01-05616-5
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
193-202
Publisher name
ČVUT v Praze
Place of publication
Praha
Event location
Malá Skála
Event date
Jun 23, 2014
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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