Small Area Estimation Using the Generalized Linear Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F10%3A00175255" target="_blank" >RIV/68407700:21340/10:00175255 - 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
Small Area Estimation Using the Generalized Linear Models
Original language description
Small area estimation is more and more demanding in these days. This statistic method is based on the use of auxiliary data collected in related small areas, let's say the small area ''borrows strength'' from other small areas. The small area is that area in which the sample size is not large enough to produce direct estimates of adequate precision. We compare linear models with fixed and random effects in this paper. There are given formulas for Empirical Best Linear Unbiased Prediction (EBLUP) and theMean Squared Error (MSE) of EBLUP. Moreover, the models are studied and compared by simulation experiment, there are given related tables and figures. Finally, both models are applied to real data.
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
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
SPMS 2010 Stochastic and Physical Monitoring Systems
ISBN
978-80-01-04641-8
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
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Publisher name
ČVUT
Place of publication
Praha
Event location
Děčín
Event date
Jun 27, 2010
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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