Estimation and hypothesis test for partial linear single-index multiplicative models
被引:0
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作者:
Jun Zhang
论文数: 0引用数: 0
h-index: 0
机构:Shenzhen University,College of Mathematics and Statistics, Shenzhen
Jun Zhang
Xia Cui
论文数: 0引用数: 0
h-index: 0
机构:Shenzhen University,College of Mathematics and Statistics, Shenzhen
Xia Cui
Heng Peng
论文数: 0引用数: 0
h-index: 0
机构:Shenzhen University,College of Mathematics and Statistics, Shenzhen
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
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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.