Empirical Likelihood for Mixed-effects Error-in-variables Model  

作　　者：Qiu-hua Chen Ping-shou Zhong Heng-jian Cui 

机构地区：[1]Mathematical & Physical Science School, North China Electric Power University, Beijing 102206, China [2]Department of Statistics and Financial Mathematics, Beijing Normal University, Beijing 100875, China

出　　处：《Acta Mathematicae Applicatae Sinica》2009年第4期561-578,共18页应用数学学报（英文版）

基　　金：Supported by the National Natural Science Foundation of China(No.10771017,No.10231030) ;the Key Project of Ministry of Education(No.309007)

摘　　要：This paper mainly introduces the method of empirical likelihood and its applications on two different models. We discuss the empirical likelihood inference on fixed-effect parameter in mixed-effects model with error-in-variables. We first consider a linear mixed-effects model with measurement errors in both fixed and random effects. We construct the empirical likelihood confidence regions for the fixed-effects parameters and the mean parameters of random-effects. The limiting distribution of the empirical log likelihood ratio at the true parameter is X2p＋q, where p, q are dimension of fixed and random effects respectively. Then we discuss empirical likelihood inference in a semi-linear error-in-variable mixed-effects model. Under certain conditions, it is shown that the empirical log likelihood ratio at the true parameter also converges to X2p＋q. Simulations illustrate that the proposed confidence region has a coverage probability more closer to the nominal level than normal approximation based confidence region.This paper mainly introduces the method of empirical likelihood and its applications on two different models. We discuss the empirical likelihood inference on fixed-effect parameter in mixed-effects model with error-in-variables. We first consider a linear mixed-effects model with measurement errors in both fixed and random effects. We construct the empirical likelihood confidence regions for the fixed-effects parameters and the mean parameters of random-effects. The limiting distribution of the empirical log likelihood ratio at the true parameter is X2p＋q, where p, q are dimension of fixed and random effects respectively. Then we discuss empirical likelihood inference in a semi-linear error-in-variable mixed-effects model. Under certain conditions, it is shown that the empirical log likelihood ratio at the true parameter also converges to X2p＋q. Simulations illustrate that the proposed confidence region has a coverage probability more closer to the nominal level than normal approximation based confidence region.

关 键 词：Confidence region empirical likelihood mixed-effects model 

分 类 号：O29[理学—应用数学]