缺失纵向数据下半参数回归模型的CC估计法  

The CC Method of the Semi-parametric Regression Model Under the Missing Longitudinal Data

作　　者：刘新乐[1] LIU Xin-le(School of Mathematics and Information Science, Henan Polytechnic University, Jiaozuo 454000 ,Chin)

机构地区：[1]河南理工大学数学与信息科学学院,河南焦作454000

出　　处：《安阳师范学院学报》2016年第5期71-74,共4页Journal of Anyang Normal University

基　　金：河南理工大学校青年基金资助项目(72511/082);河南理工大学校示范教师教改专项资助项目(72307/001)

摘　　要：缺失数据模型问题和纵向数据模型问题一直是统计学的热点之一,但对于纵向数据缺失情况的模型研究较少.本文针对纵向数据缺失情况提出了缺失纵向数据下的半参数回归模型,使用CC(Complete-Case)方法将所有含数据缺失的项删除,仅对余下的"完全"样本按二阶段估计的方法进行统计推断,得到了参数向量和非参数向量的二阶段估计的最终估计βr和gr(t),并证明这些估计量满足渐近正态性质.并且通过数据模拟形式说明了这个估计方法的可行性.The issues of the missing data model and the longitudinal data model have been one of the hotspots of the statistics,but the study of the model of missing longitudinal data is very few.The semi-parametric re-gression model of missing longitudinal data is proposed in this thesis and the solutions is given：For missing longitudinal data,all items will be deleted in this thesis which contains lossing data using the CC method,and only remaining“full”sample.By the second stage estination method for statistical inference,the ultimate esti-mates of parametric and nonparametric vector are got by using the two stages estimate.And the asymptotic nor-mal properties of these estimators is proved.And the data simulation shows that the estimation method is feasi-ble.

关 键 词：缺失纵向数据 半参数回归模型 CC方法 相合性 渐近正态性 

分 类 号：O212.7[理学—概率论与数理统计]