Bootstrap confidence intervals in functional nonparametric regression under dependence

被引：30

作者：

Rana, Paula ^{[1
]}

Aneiros, German ^{[1
]}

Vilar, Juan ^{[1
]}

Vieu, Philippe ^{[2
]}

机构：

[1] Univ A Coruna, Dept Matemat, La Coruna, Spain

[2] Univ Paul Sabatier, Inst Math, Toulouse, France

来源：

ELECTRONIC JOURNAL OF STATISTICS | 2016年 / 10卷 / 02期

关键词：

Functional data; bootstrap; nonparametric regression; confidence intervals; alpha-mixing; TIME-SERIES PREDICTION; MODELS;

D O I：

10.1214/16-EJS1156

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：

This paper considers naive and wild bootstrap procedures to construct pointwise confidence intervals for a nonparametric regression function when the predictor is of functional nature and when the data are dependent. Assuming alpha-mixing conditions on the sample, the asymptotic validity of both procedures is obtained. A simulation study shows promising results when finite sample sizes are used, while an application to electricity demand data illustrates its usefulness in practice.

引用

页码：1973 / 1999

页数：27

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