A modified nested-error regression model for small area estimation

被引：1

作者：

Herrador, M. ^{[1
]}

Esteban, M. D. ^{[2
]}

Hobza, T. ^{[3
]}

Morales, D. ^{[2
]}

机构：

[1] Inst Nacl Estadist, Madrid, Spain

[2] Miguel Hernandez Univ Elche, Ctr Operat Res, Elche, Spain

[3] Czech Tech Univ, Dept Math, CR-16635 Prague, Czech Republic

来源：

STATISTICS | 2013年 / 47卷 / 02期

关键词：

small area estimation; linear mixed models; nested-error regression model; fixed effects; random effects; EBLUP; outliers; MEAN SQUARED ERROR; PREDICTION;

D O I：

10.1080/02331888.2011.599068

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A nested-error regression model having both fixed and random effects is introduced to estimate linear parameters of small areas. The model is applicable to data having a proportion of domains where the variable of interest cannot be described by a standard linear mixed model. Algorithms and formulas to fit the model, to calculate EBLUP and to estimate mean-squared errors are given. A Monte Carlo simulation experiment is presented to illustrate the gain of precision obtained by using the proposed model and to obtain some practical conclusions. A motivating application to Spanish Labour Force Survey data is also given.

引用

页码：258 / 273

页数：16

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