Local linear regression for functional data

被引：0
|
作者：
A. Berlinet
A. Elamine
A. Mas
机构：
[1] Université Montpellier 2,Département de Mathématiques, CC 051
来源：
Annals of the Institute of Statistical Mathematics | 2011年 / 63卷
关键词：
Functional data; Regression model; Kernel; Mean square error; Small ball probability; Inverse problem;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We study a non-linear regression model with functional data as inputs and scalar response. We propose a pointwise estimate of the regression function that maps a Hilbert space onto the real line by a local linear method and derive its asymptotic mean square error. Computations involve a linear inverse problem as well as a representation of the small ball probability of the data and are based on recent advances in this area.
引用
收藏
页码：1047 / 1075
页数：28
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