title: Hidden Frequency Estimation with Data Tapers
creator: Chen, Zhao-Guo
creator: Wu, Ka Ho
creator: Dahlhaus, Rainer
subject: 510
subject: 510 Mathematics
description: Detecting and estimating hidden frequencies have long been recognized as an important problem in time series. This paper studies the asymptotic theory for two methods of high-precision estimation of hidden frequencies (secondary analysis method and maximum periodogram method) under the premise of using a data taper. In ordinary situations, a data taper may reduce the estimation precision slightly. However, when there are high peaks in thespectral density of the noise or other strong hidden periodicities with frequencies close to the hidden frequency of interest, the procedures of detection of the existence and the estimation for the hidden frequency of interest fail if data are non-tapered whereas they may work well if the data are tapered. The theoretical results are verified by some simulated examples.
publisher: Wiley-Blackwell
date: 2000-03
type: Article
type: info:eu-repo/semantics/article
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/20794/1/Beitrag.54.pdf
identifier: DOI:10.11588/heidok.00020794
identifier: urn:nbn:de:bsz:16-heidok-207946
identifier:   Chen, Zhao-Guo ; Wu, Ka Ho ; Dahlhaus, Rainer  (2000) Hidden Frequency Estimation with Data Tapers.  Journal of Time Series Analysis, 21 (2).  pp. 113-142.  ISSN 1467-9892     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/20794/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: eng