Local Least Product Relative Error Estimation for Varying Coefficient Multiplicative Regression Model

被引：0
作者：
Da-hai Hu
机构：
[1] University of Science and Technology of China,School of Management
来源：
Acta Mathematicae Applicatae Sinica, English Series | 2019年 / 35卷
关键词：
varying coefficient model; multiplicative regression model; relative error; kernel smoothing; 62G05; 62G08;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this article, we consider the varying coefficient multiplicative regression model, which is very useful to model the positive response. The criterion of least product relative error (LPRE) is extended to the varying coefficient multiplicative regression model by kernel smoothing techniques. Consistency and asymptotic normality of the proposed estimator are established. Some numerical simulations are carried out to assess the performance of the proposed estimator. As an illustration, the ethanol data is analyzed.
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收藏
页码：274 / 286
页数：12
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共 47 条
[21]   Projection-type estimation for varying coefficient regression models [J].
Lee, Young K. ;
Mammen, Enno ;
Park, Byeong U. .
BERNOULLI, 2012, 18 (01) :177-205
[22]   Boosted Varying-Coefficient Regression Models for Product Demand Prediction [J].
Wang, Jianqiang C. ;
Hastie, Trevor .
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2014, 23 (02) :361-382
[23]   Functional local linear estimate for functional relative-error regression [J].
Chahad A. ;
Ait-Hennani L. ;
Laksaci A. .
Journal of Statistical Theory and Practice, 2017, 11 (4) :771-789
[24]   Measuring the symmetry of model errors for varying coefficient regression models based on correlation coefficient [J].
Gai, Yujie ;
Wei, Yusheng ;
Zhang, Jun ;
Chen, Aixian .
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2022, 51 (05) :2235-2251
[25]   Nonparametric estimation of varying coefficient error-in-variable models with validation sampling [J].
Lv, Yazhao ;
Zhang, Riquan ;
Huang, Zhensheng .
JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2011, 141 (10) :3323-3344
[26]   Functional data analysis: estimation of the relative error in functional regression under random left-truncation model [J].
Altendji, Belkais ;
Demongeot, Jacques ;
Laksaci, Ali ;
Rachdi, Mustapha .
JOURNAL OF NONPARAMETRIC STATISTICS, 2018, 30 (02) :472-490
[27]   Weighted composite quantile regression estimation and variable selection for varying coefficient models with heteroscedasticity [J].
Yang, Hu ;
Lv, Jing ;
Guo, Chaohui .
JOURNAL OF THE KOREAN STATISTICAL SOCIETY, 2015, 44 (01) :77-94
[28]   Weighted composite quantile regression estimation and variable selection for varying coefficient models with heteroscedasticity [J].
Hu Yang ;
Jing Lv ;
Chaohui Guo .
Journal of the Korean Statistical Society, 2015, 44 :77-94
[29]   Local linear estimation for covariate-adjusted varying-coefficient models [J].
Lu, Yiqiang ;
Li, Feng ;
Feng, Sanying .
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2019, 48 (15) :3816-3835
[30]   Composite quantile regression estimation for varying coefficient panel data models with fixed effects based on auxiliary regression [J].
Yu, Shenao ;
Zhao, Xu ;
Yang, Yiping .
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2025, 95 (10) :2235-2258
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