Functional linear model

被引：407

作者：

Cardot, H

Ferraty, F

Sarda, P

机构：

[1] INRA, Unit Biometrie & Intelligence Artificielle, F-31326 Castanet Tolosan, France

[2] Univ Toulouse 3, Lab Stat & Probabil, CNRS, UMR C5583, F-31062 Toulouse, France

来源：

STATISTICS & PROBABILITY LETTERS | 1999年 / 45卷 / 01期

关键词：

functional linear model; functional data analysis; Hilbert spaces; convergence;

D O I：

10.1016/S0167-7152(99)00036-X

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 study a regression model in which explanatory variables are sampling points of a continuous-time process. We propose an estimator of regression by means of a Functional Principal Component Analysis analogous to the one introduced by Bosq [(1991) NATO, ASI Series, pp. 509-529] in the case of Hilbertian AR processes. Both convergence in probability and almost sure convergence of this estimator are stated. (C) 1999 Elsevier Science B.V. All rights reserved.

引用

页码：11 / 22

页数：12

共 14 条

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