Mean-squared errors of small-area estimators under a unit-level multivariate model

被引：4

作者：

Baillo, Amparo ^{[2
]}

Molina, Isabel ^{[1
]}

机构：

[1] Univ Carlos III Madrid, Dept Estadist, Madrid, Spain

[2] Univ Autonoma Madrid, Dept Matemat, Madrid, Spain

来源：

STATISTICS | 2009年 / 43卷 / 06期

关键词：

best linear unbiased predictor; maximum likelihood; mean-squared error; multivariate mixed linear model; small area; MIXED LINEAR-MODELS; PREDICTION;

D O I：

10.1080/02331880802605304

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：

This work deals with estimating the vector of means of certain characteristics of small areas. In this context, a unit level multivariate model with correlated sampling errors is considered. An approximation is obtained for the mean-squared and cross-product errors of the empirical best linear unbiased predictors of the means, when model parameters are estimated either by maximum likelihood (ML) or by restricted ML. This approach has been implemented on a Monte Carlo study using social and labour data from the Spanish Labour Force Survey.

引用

页码：553 / 569

页数：17

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