Generalized linear mixed models for small area estimation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F19%3A00335961" target="_blank" >RIV/68407700:21340/19:00335961 - isvavai.cz</a>

Výsledek na webu

<a href="http://gams.fjfi.cvut.cz/spms2019" target="_blank" >http://gams.fjfi.cvut.cz/spms2019</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Generalized linear mixed models for small area estimation

Popis výsledku v původním jazyce

Small area estimation is a field of statistics which deals with the problem of obtaining reliable estimates of characteristics of interest in situations when the sample is divided into domains for which the sample sizes are often small. For the use in this field a new unit-level logit mixed model is proposed. The model uses fixed effects for areas with larger sample sizes and models the rest of the domains by random effects. In order to predict area means empirical best predictor and plug-in predictor are used and compared via a simulation experiment. Simulation studies are carried out in order to compare the quality of predictions acquired from the proposed model with predictions obtained from a binomial logit-mixed model which only uses random effects to model the domains. The two models are applied to the estimation of poverty risks in counties of the region of Valencia, Spain, and their predictions are compared.

Název v anglickém jazyce

Generalized linear mixed models for small area estimation

Popis výsledku anglicky

Small area estimation is a field of statistics which deals with the problem of obtaining reliable estimates of characteristics of interest in situations when the sample is divided into domains for which the sample sizes are often small. For the use in this field a new unit-level logit mixed model is proposed. The model uses fixed effects for areas with larger sample sizes and models the rest of the domains by random effects. In order to predict area means empirical best predictor and plug-in predictor are used and compared via a simulation experiment. Simulation studies are carried out in order to compare the quality of predictions acquired from the proposed model with predictions obtained from a binomial logit-mixed model which only uses random effects to model the domains. The two models are applied to the estimation of poverty risks in counties of the region of Valencia, Spain, and their predictions are compared.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10103 - Statistics and probability

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of SPMS 2019 - Stochastic and Physical Monitoring Systems

ISBN

978-80-01-06659-1

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

57-64

Název nakladatele

Česká technika - nakladatelství ČVUT

Místo vydání

Praha

Místo konání akce

Dobřichovice

Datum konání akce

20. 6. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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