Local least product relative error estimation for single-index varying-coefficient multiplicative model with positive responses

被引:5
|
作者
Chen, Yinjun [1 ]
Liu, Huilan [1 ]
Ma, Junjie [1 ]
机构
[1] Guizhou Univ, Sch Math & Stat, Guiyang 550025, Peoples R China
基金
中国国家自然科学基金; 安徽省自然科学基金;
关键词
Asymptotic normality; Least product relative error; Multiplicative model; Single-index multiplicative model; Single-index varying-coefficient; EMPIRICAL LIKELIHOOD; VARIABLE SELECTION; REGRESSION; ASYMPTOTICS; ROBUST;
D O I
10.1016/j.cam.2022.114478
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, we study the single-index varying-coefficient multiplicative model (SIVCMM) for analyzing data with positive response. Based on the least product relative error (LPRE) and local kernel smoothing methods, an efficient approach is proposed for estimating the unknown parameter vector and nonparametric functions arising in SIVCMM. Furthermore, the convergence properties of the proposed estimators are established. Finally, numerical studies are conducted to test the performance of the proposed approach, and a real data analysis is presented to illustrate the new estimator's efficiency in practical computation. (C) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页数:17
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