Missing responses at random in functional single index model for time series data

被引：0
作者：
Nengxiang Ling
Lilei Cheng
Philippe Vieu
Hui Ding
机构：
[1] Hefei University of Technology,School of Mathematics
[2] Institut de Mathématiques,School of Economics
[3] Université Paul Sabatier,undefined
[4] Nanjing University of Finance and Economics,undefined
来源：
Statistical Papers | 2022年 / 63卷
关键词：
Functional single index model; Uniform almost complete convergence rate; Asymptotic normality; Strong mixing dependence; Missing responses at random;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, we first investigate the estimation of the functional single index regression model with missing responses at random for strong mixing time series data. More precisely, the uniform almost complete convergence rate and asymptotic normality of the estimator are obtained respectively under some general conditions. Then, some simulation studies are carried out to show the finite sample performances of the estimator. Finally, a real data analysis about the sea surface temperature is used to illustrate the effectiveness of our methodology.
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页码：665 / 692
页数：27
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