Linear prediction in functional data analysis

被引:12
|
作者
Shin, Hyejin
Hsing, Tailen [1 ]
机构
[1] Univ Michigan, Dept Stat, Ann Arbor, MI 48103 USA
基金
新加坡国家研究基金会;
关键词
Hilbert space; Unbounded linear functional; Principal components; Convergence rate; CONVERGENCE-RATES; REGRESSION; ESTIMATORS;
D O I
10.1016/j.spa.2012.06.014
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 paper we introduce a new perspective of linear prediction in the functional data context that predicts a scalar response by observing a functional predictor. This perspective broadens the scope of functional linear prediction currently in the literature, which is exclusively focused on the functional linear regression model. It also provides a natural link to the classical linear prediction theory. Based on this formulation, we derive the convergence rate of the optimal mean squared predictor. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:3680 / 3700
页数:21
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