Tests for the variance parameter in the Fay-Herriot model

被引:2
|
作者
Marhuenda, Y. [1 ]
Morales, D. [1 ]
Pardo, M. C. [2 ]
机构
[1] Univ Miguel Hernandez Elche, Ctr Invest Operat, Elche, Spain
[2] Univ Complutense Madrid, Dept Estadist & Invest Operat 1, Madrid, Spain
关键词
Fay-Herriot model; small area estimation; zero variance component; likelihood ratio test; Monte Carlo simulation; LIKELIHOOD RATIO TESTS; SMALL-AREA ESTIMATION; REGRESSION;
D O I
10.1080/02331888.2015.1016026
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
The Fay-Herriot model is a linear mixed model that plays a relevant role in small area estimation (SAE). Under the SAE set-up, tools for selecting an adequate model are required. Applied statisticians are often interested on deciding if it is worthwhile to use a mixed effect model instead of a simpler fixed-effect model. This problem is not standard because under the null hypothesis the random effect variance is on the boundary of the parameter space. The likelihood ratio test and the residual likelihood ratio test are proposed and their finite sample distributions are derived. Finally, we analyse their behaviour under simulated scenarios and we also apply them to real data.
引用
收藏
页码:27 / 42
页数:16
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