EMPIRICAL LIKELIHOOD INFERENCE FOR LOGISTIC EQUATION WITH RANDOM PERTURBATION

作     者：HU Xuemei 

作者机构：School of Mathematics and StatisticsChongQing Technology and Business University Academy of Mathematics and Systems ScienceChinese Academy of Sciences 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)

年 卷 期：2014年第27卷第2期

页      面：350-359页

核心收录：

学科分类：02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 0701[理学-数学] 

基　　金：supported by the National Natural Science Foundation of China under Grant No.11101452 the Natural Science Foundation Project of CQ CSTC under Grant No.2012jjA00035 the National Basic Research Program of China under Grant No.2011CB808000 

主　　题：Empirical likelihood ratio statistic estimating equations logistic equation with randomperturbation maximum empirical likelihood estimations maximum likelihood estimation. 

摘      要：Empirical likelihood(EL) combined with estimating equations(EE) provides a modern semi-parametric alternative to classical estimation techniques such as maximum likelihood estimation(MLE). This paper not only uses closed form of conditional expectation and conditional variance of Logistic equation with random perturbation to perform maximum empirical likelihood estimation(MELE) for the model parameters, but also proposes an empirical likelihood ratio statistic(ELRS) for hypotheses concerning the interesting parameter. Monte Carlo simulation results show that MELE and ELRS provide competitive performance to parametric alternatives.