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, T
Hirata, Y
Small, M
Issue Date: 17-Oct-2006
Source: 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.
Keywords: Correlation methods
Data acquisition
Numerical methods
Time series analysis
Publisher: American Physical Society
Journal: Physical review. E, Statistical, nonlinear, and soft matter physics 
ISSN: 1539-3755
EISSN: 1550-2376
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/
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Nakamura_Testing_Multivariate_Time.pdf1.32 MBAdobe PDFView/Open
Access
View full-text via PolyU eLinks SFX Query
Show full item record
PIRA download icon_1.1View/Download Full Text

SCOPUSTM   
Citations

7
Last Week
0
Last month
0
Citations as of Aug 10, 2020

WEB OF SCIENCETM
Citations

7
Last Week
0
Last month
0
Citations as of Aug 11, 2020

Page view(s)

325
Last Week
1
Last month
Citations as of Aug 10, 2020

Download(s)

221
Citations as of Aug 10, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.