Testing for correlation structures in short-term variabilities with long-term trends of multivariate time series

Tomomichi Nakamura, Yoshito Hirata, and Michael Small
Phys. Rev. E 74, 041114 – Published 17 October 2006

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.

  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
  • Received 15 June 2006

DOI:https://doi.org/10.1103/PhysRevE.74.041114

©2006 American Physical Society

Authors & Affiliations

Tomomichi Nakamura1,*, Yoshito Hirata2,†, and Michael Small1,‡

  • 1Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
  • 2Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan

  • *Electronic address: entomo@eie.polyu.edu.hk
  • Electronic address: yoshito@sat.t.u-tokyo.ac.jp
  • Electronic address: ensmall@polyu.edu.hk

Article Text (Subscription Required)

Click to Expand

References (Subscription Required)

Click to Expand
Issue

Vol. 74, Iss. 4 — October 2006

Reuse & Permissions
Access Options
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review E

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×