Penalized relative error estimation of functional multiplicative regression models with locally sparse properties

被引：0
|
作者：
Ruiya Fan
Shuguang Zhang
Yaohua Wu
机构：
[1] University of Science and Technology of China,Department of Statistics and Finance
来源：
Journal of the Korean Statistical Society | 2022年 / 51卷
关键词：
Variable selection; Functional multiplicative regression model; Functional relative errors;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Based on functional relative errors, we develop a functional penalized smooth least absolute relative error (FPSLARE) criterion for locally sparse functional multiplicative regression models. Under some mild conditions, we establish the oracle properties of FPSLARE estimators, including the consistency of model selection and the asymptotic normality for the estimator. In addition, numerical studies and a real data analysis are carried out to evaluate the performance of the proposed approaches.
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收藏
页码：666 / 691
页数：25
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