Small area estimation of additive parameters under unit-level generalized linear mixed models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F20%3A00336508" target="_blank" >RIV/68407700:21340/20:00336508 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.2436/20.8080.02.93" target="_blank" >https://doi.org/10.2436/20.8080.02.93</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2436/20.8080.02.93" target="_blank" >10.2436/20.8080.02.93</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Small area estimation of additive parameters under unit-level generalized linear mixed models

Popis výsledku v původním jazyce

Average incomes and poverty proportions are additive parameters obtained as averages of a given function of an income variable. As the variable income has an asymmetric distribution, it is not properly modeled via normal distributions. When dealing with this type of variables, a first option is to apply transformations that approach normality. A second option is to use nonsymmetric distributions from the exponential family. This paper proposes unit-level generalized linear mixed models for modeling asymmetric positive variables and for deriving three types of predictors of small area additive parameters, called empirical best, marginal and plug-in. The parameters of the introduced model are estimated by applying the maximum likelihood method to the Laplace approximation of the likelihood. The mean squared errors of the predictors are estimated by parametric bootstrap. The introduced methodology is applied and illustrated under unit-level gamma mixed models. Some simulation experiments are carried out to study the behavior of the fitting algorithm, the small area predictors and the bootstrap estimator of the mean squared errors. By using data of the Spanish living condition survey of 2013, an application to the estimation of average incomes and poverty proportions in counties of the region of Valencia is given.

Název v anglickém jazyce

Small area estimation of additive parameters under unit-level generalized linear mixed models

Popis výsledku anglicky

Average incomes and poverty proportions are additive parameters obtained as averages of a given function of an income variable. As the variable income has an asymmetric distribution, it is not properly modeled via normal distributions. When dealing with this type of variables, a first option is to apply transformations that approach normality. A second option is to use nonsymmetric distributions from the exponential family. This paper proposes unit-level generalized linear mixed models for modeling asymmetric positive variables and for deriving three types of predictors of small area additive parameters, called empirical best, marginal and plug-in. The parameters of the introduced model are estimated by applying the maximum likelihood method to the Laplace approximation of the likelihood. The mean squared errors of the predictors are estimated by parametric bootstrap. The introduced methodology is applied and illustrated under unit-level gamma mixed models. Some simulation experiments are carried out to study the behavior of the fitting algorithm, the small area predictors and the bootstrap estimator of the mean squared errors. By using data of the Spanish living condition survey of 2013, an application to the estimation of average incomes and poverty proportions in counties of the region of Valencia is given.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/EF16_019%2F0000778" target="_blank" >EF16_019/0000778: Centrum pokročilých aplikovaných přírodních věd</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název periodika

SORT

ISSN

1696-2281

e-ISSN

2013-8830

Svazek periodika

44

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

ES - Španělské království

Počet stran výsledku

36

Strana od-do

3-38

Kód UT WoS článku

000544353100001

EID výsledku v databázi Scopus

2-s2.0-85090207684