Variable selection for semiparametric random-effects conditional density models with longitudinal data
Variable selection for semiparametric random-effects conditional density models with longitudinal data
复制标题
纵向数据半参数随机效应条件密度模型的变量选择
DOI：
10.1080/03610926.2018.1554130
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Liu Tianqing
中科院分区：
文献类型：
--
作者：
Yuan Xiaohui;Wang Yue;Liu Tianqing
Abstract Variable selection using regularization approaches is an essential part of any statistical analysis and yet has been somewhat neglected for the semiparametric random-effects conditional density (RECD) models with longitudinal data. In this paper, we show how the regularization approach for variable selection can be adapted to the RECD models with longitudinal data. The computational and theoretical properties for variable selection consistency are established. Comprehensive simulation studies and a real data analysis further demonstrate the merits of our approach.
