Nonparametric M-estimation for Functional Stationary Ergodic Data

被引：0
|
作者：
Xian-zhu XIONG [1 ]
Zheng-yan LIN [2 ]
机构：
[1] College of Mathematics and Computer Science, Fuzhou University
[2] Department of Mathematics, Zhejiang University
来源：
Acta Mathematicae Applicatae Sinica | 2019年 / 35卷 / 03期
基金：
中国国家自然科学基金;
关键词：
nonparametric M-estimator; functional stationary ergodic data; weak consistency; asymptotic normality;
D O I：
暂无
中图分类号：
O212 [数理统计];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
This paper considers a nonparametric M-estimator of a regression function for functional stationary ergodic data. More precisely, in the ergodic data setting, we consider the regression of a real random variable Y over an explanatory random variable X taking values in some semi-metric abstract space. Under some mild conditions, the weak consistency and the asymptotic normality of the M-estimator are established. Furthermore,a simulated example is provided to examine the finite sample performance of the M-estimator.
引用
收藏
页码：491 / 512
页数：22
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