Automatic estimation procedure in partial linear model with functional data

被引：34

作者：

Aneiros-Perez, German ^{[1
]}

Vieu, Philippe ^{[2
]}

机构：

[1] Univ A Coruna, Fac Informat, La Coruna 15071, Spain

[2] Univ Toulouse 3, F-31062 Toulouse, France

来源：

STATISTICAL PAPERS | 2011年 / 52卷 / 04期

关键词：

Bandwidth selection; Cross-validation; Functional data; Partial linear regression; TIME-SERIES PREDICTION; NONPARAMETRIC REGRESSION; BANDWIDTH SELECTION;

D O I：

10.1007/s00362-009-0280-2

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：

Partial linear modelling ideas have recently been adapted to situations when functional data are observed. This paper aims to complete the study of such model by proposing a fully automatic estimation procedure. This is achieved by constructing a data-driven method to choose the smoothing parameters entered in the nonparametric components of the model. The asymptotic optimality of the method is stated and its practical interest is illustrated on finite size Monte Carlo simulated samples.

引用

页码：751 / 771

页数：21

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