Bootstrap confidence bands for spectra and cross-spectra

Politis, Dimitris Nicolas; Romano, J. P.; Lai, T. -L

doi:10.1109/78.134482

dc.contributor.author	Politis, Dimitris Nicolas	en
dc.contributor.author	Romano, J. P.	en
dc.contributor.author	Lai, T. -L	en
dc.creator	Politis, Dimitris Nicolas	en
dc.creator	Romano, J. P.	en
dc.creator	Lai, T. -L	en
dc.date.accessioned	2019-12-02T10:37:56Z
dc.date.available	2019-12-02T10:37:56Z
dc.date.issued	1992
dc.identifier.issn	1053-587X
dc.identifier.uri	http://gnosis.library.ucy.ac.cy/handle/7/57536
dc.description.abstract	A new nonparametric method for setting confidence intervals and confidence bands for spectra and cross-spectra of stationary weakly dependent time series is presented. The proposed methodology involves using a bootstrap resampling scheme that was recently developed for use in time series problems. A computing algorithm is provided, along with guidelines on its practical application. Finally, results of simulations with artificially generated data are shown as an illustration of the method’s potential. © 1992 IEEE	en
dc.source	IEEE Transactions on Signal Processing	en
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-0026863452&doi=10.1109%2f78.134482&partnerID=40&md5=7e9b203939a22f525c54bffc39da02dc
dc.subject	Computer Simulation	en
dc.subject	Probability	en
dc.subject	Confidence Intervals	en
dc.subject	Spectrum Analysis	en
dc.subject	ARMA Time Series	en
dc.subject	Bootstrap Confidence Bands	en
dc.subject	Bootstrap Resampling	en
dc.subject	Mathematical Statistics - Monte Carlo Methods	en
dc.subject	Signal Processing - Sampling	en
dc.subject	Statistical Methods - Time Series Analysis	en
dc.subject	Weakly Dependent Time Series	en
dc.title	Bootstrap confidence bands for spectra and cross-spectra	en
dc.type	info:eu-repo/semantics/article
dc.identifier.doi	10.1109/78.134482
dc.description.volume	40
dc.description.issue	5
dc.description.startingpage	1206
dc.description.endingpage	1215
dc.author.faculty	Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.department	Τμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics
dc.type.uhtype	Article	en
dc.description.notes	<p>Cited By :22</p>	en
dc.source.abbreviation	IEEE Trans Signal Process	en

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