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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/4829

Title: Testing for correlation structures in short-term variabilities with long-term trends of multivariate time series
Authors: Nakamura, Tomomichi
Hirata, Yoshito
Small, Michael
Subjects: Correlation methods
Data acquisition
Numerical methods
Time series analysis
Issue Date: 17-Oct-2006
Publisher: American Physical Society
Citation: Physical review E, statistical, nonlinear, and soft matter physics, Oct. 2006, v. 74, no. 4, 041114, p. 1-8.
Abstract: We describe a method for identifying correlation structures in irregular fluctuations (short-term variabilities) of multivariate time series, even if they exhibit long-term trends. This method is based on the previously proposed small shuffle surrogate method. The null hypothesis addressed by this method is that there is no short-term correlation structure among data or that the irregular fluctuations are independent. The method is demonstrated for numerical data generated by known systems and applied to several experimental time series.
Description: DOI: 10.1103/PhysRevE.74.041114
Rights: Physical Review E © 2006 The American Physical Society. The Journal's web site is located at http://pre.aps.org/
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/4829
ISSN: 1539-3755 (print)
1550-2376 (online)
Appears in Collections:EIE Journal/Magazine Articles

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