On bootstrapping kernel spectral estimates
type: Item
instance of: scholarly article
title: On bootstrapping kernel spectral estimates
zbMATH Open document ID: 0757.62048
author: Jürgen Franke
author: Wolfgang K. Härdle
published in: The Annals of Statistics
publication date: 1992-09-27T00:00:00Z
review text: This paper considers the problem of determining the statistical characteristics (such as probability distribution and confidence limits) of a kernel spectral density estimator, by using the bootstrap approach. A simple and natural bootstrapping scheme based on resampling the data periodogram ordinates (appropriately normalized) is introduced. The validity of this bootstrapping scheme is established under mild conditions, and also illustrated by means of a Monte-Carlo simulation study. Applications of the proposed bootstrapping scheme to the problem of determining confidence intervals for and selecting the local bandwidth in kernel spectral estimation are also discussed.
reviewed by: Petre Stoica
Mathematics Subject Classification ID: 62M15
Mathematics Subject Classification ID: 62G09
Mathematics Subject Classification ID: 62G07
zbMATH DE Number: 61832
zbMATH Keywords: time series
zbMATH Keywords: bandwidth selection
zbMATH Keywords: confidence limits
zbMATH Keywords: kernel spectral density estimator
zbMATH Keywords: bootstrap
zbMATH Keywords: resampling
zbMATH Keywords: periodogram
zbMATH Keywords: Monte-Carlo simulation
zbMATH Keywords: confidence intervals
zbMATH Keywords: local bandwidth
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/aos/1176348515
OpenAlex ID: W1977648299
DOI: 10.1214/AOS/1176348515
description: scientific article; zbMATH DE number 61832