Minimax rate in prediction for functional principal component regression

被引：0

作者：

Yang, Guangren ^{[1
]}

Lin, Hongmei ^{[2
]}

Lian, Heng ^{[3
]}

机构：

[1] Jinan Univ, Sch Econ, Dept Stat, Guangzhou, Guangdong, Peoples R China

[2] Shanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai 201620, Peoples R China

[3] City Univ Hong Kong, Dept Math, Hong Kong, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2021年 / 50卷 / 05期

关键词：

Functional linear regression; functional principal component analysis; minimax convergence rate; CONVERGENCE; MODELS;

D O I：

10.1080/03610926.2019.1649429

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this short paper, we consider the convergence rate of functional linear regression in prediction loss. For upper bound we consider estimation of the slope function based on functional principal component analysis. Lower bound is also obtained that shows the convergence rate obtained using functional principal component regression is optimal.

引用

页码：1240 / 1249

页数：10

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