Estimation and hypothesis test for partial linear single-index multiplicative models

被引:0
|
作者
Jun Zhang
Xia Cui
Heng Peng
机构
[1] Shenzhen University,College of Mathematics and Statistics, Shenzhen
[2] Guangzhou University,Hong Kong Joint Research Center for Applied Statistical Sciences, Institute of Statistical Sciences
[3] The Hong Kong Baptist University,School of Economics and Statistics
来源
Annals of the Institute of Statistical Mathematics | 2020年 / 72卷
关键词
Local linear smoothing; Model checking; Profile least product relative error estimator; Single-index; Variable selection;
D O I
暂无
中图分类号
学科分类号
摘要
Estimation and hypothesis test for partial linear single-index multiplicative models are considered in this paper. To estimate unknown single-index parameter, we propose a profile least product relative error estimator coupled with a leave-one-component-out method. To test a hypothesis on the parametric components, a Wald-type test statistic is proposed. We employ the smoothly clipped absolute deviation penalty to select relevant variables. To study model checking problem, we propose a variant of the integrated conditional moment test statistic by using linear projection weighting function, and we also suggest a bootstrap procedure for calculating critical values. Simulation studies are conducted to demonstrate the performance of the proposed procedure and a real example is analyzed for illustration.
引用
收藏
页码:699 / 740
页数:41
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