Application of an area level model to small area estimation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F10%3A00175113" target="_blank" >RIV/68407700:21340/10:00175113 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Application of an area level model to small area estimation

Popis výsledku v původním jazyce

In this contribution we extend the Fay-Herriot model to an area level linear regression model with random intercepts having one of two possible variances. The model is applicable to data having a large 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. This is generally the case when domains are constructed by crossing geographical characteristics with sex. Estimation procedures for the variance components and regression parameters are considered and empirical best linear unbiased predictors (EBLUP) of domain parameters are derived as well as estimates of the mean square error of the EBLUP. Monte Carlo simulation experiments are presented to illustrate thegain of precision obtained by using the proposed model and to get some practical conclusions. A motivating application to Spanish Labour Force Survey data is also given.

Název v anglickém jazyce

Application of an area level model to small area estimation

Popis výsledku anglicky

In this contribution we extend the Fay-Herriot model to an area level linear regression model with random intercepts having one of two possible variances. The model is applicable to data having a large 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. This is generally the case when domains are constructed by crossing geographical characteristics with sex. Estimation procedures for the variance components and regression parameters are considered and empirical best linear unbiased predictors (EBLUP) of domain parameters are derived as well as estimates of the mean square error of the EBLUP. Monte Carlo simulation experiments are presented to illustrate thegain of precision obtained by using the proposed model and to get some practical conclusions. A motivating application to Spanish Labour Force Survey data is also given.

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2010

Kód důvěrnosti údajů

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

Název statě ve sborníku

SPMS 2010 Stochastic and Physical Monitoring Systems

ISBN

978-80-01-04641-8

ISSN

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e-ISSN

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Počet stran výsledku

9

Strana od-do

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Název nakladatele

ČVUT

Místo vydání

Praha

Místo konání akce

Děčín

Datum konání akce

27. 6. 2010

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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