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Hidden Frequency Estimation with Data Tapers

Chen, Zhao-Guo ; Wu, Ka Ho ; Dahlhaus, Rainer

In: Journal of Time Series Analysis, 21 (March 2000), Nr. 2. pp. 113-142. ISSN 1467-9892

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Abstract

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.

Document type: Article
Journal or Publication Title: Journal of Time Series Analysis
Volume: 21
Number: 2
Publisher: Wiley-Blackwell
Place of Publication: Oxford
Date Deposited: 30 May 2016 08:23
Date: March 2000
ISSN: 1467-9892
Number of Pages: 45
Page Range: pp. 113-142
Faculties / Institutes: The Faculty of Mathematics and Computer Science > Institut für Mathematik
DDC-classification: 510 Mathematics
Uncontrolled Keywords: Central limit theorem; Frequency leakage; Fourier transformation; Law of the iterated logarithm; Periodogram; Secondary analysis
Series: Beiträge zur Statistik > Beiträge
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