Wavelet-M-Estimation for Time-Varying Coefficient Time Series Models

被引：2
|
作者：
Zhou, Xingcai [1 ,2 ]
Zhu, Fangxia [3 ]
机构：
[1] Nanjing Audit Univ, Inst Stat & Data Sci, Nanjing, Jiangsu, Peoples R China
[2] Southeast Univ, Sch Econ & Management, Nanjing, Jiangsu, Peoples R China
[3] Chuzhou Univ, Sch Math & Finance, Chuzhou, Anhui, Peoples R China
来源：
DISCRETE DYNAMICS IN NATURE AND SOCIETY | 2020年 / 2020卷
基金：
中国博士后科学基金;
关键词：
STATISTICAL-INFERENCE; REGRESSION;
D O I：
10.1155/2020/1025452
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
This paper proposes wavelet-M-estimation for time-varying coefficient time series models by using a robust-type wavelet technique, which can adapt to local features of the time-varying coefficients and does not require the smoothness of the unknown time-varying coefficient. The wavelet-M-estimation has the desired asymptotic properties and can be used to estimate conditional quantile and to robustify the usual mean regression. Under mild assumptions, the Bahadur representation and the asymptotic normality of wavelet-M-estimation are established.
引用
收藏
页数：11
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