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2016 Bootstrap confidence intervals in functional nonparametric regression under dependence
Paula Raña, Germán Aneiros, Juan Vilar, Philippe Vieu
Electron. J. Statist. 10(2): 1973-1999 (2016). DOI: 10.1214/16-EJS1156

Abstract

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.

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Paula Raña. Germán Aneiros. Juan Vilar. Philippe Vieu. "Bootstrap confidence intervals in functional nonparametric regression under dependence." Electron. J. Statist. 10 (2) 1973 - 1999, 2016. https://doi.org/10.1214/16-EJS1156

Information

Received: 1 December 2015; Published: 2016
First available in Project Euclid: 18 July 2016

zbMATH: 1346.62082
MathSciNet: MR3522666
Digital Object Identifier: 10.1214/16-EJS1156

Subjects:
Primary: 62G08, 62G09, 62G20

Rights: Copyright © 2016 The Institute of Mathematical Statistics and the Bernoulli Society

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Vol.10 • No. 2 • 2016
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