Volume 101, Number 2, February 2013
|Number of page(s)||6|
|Published online||07 February 2013|
Quantifying different degrees of coupling in detrended cross-correlation analysis
1 Institute of Clinical Physiology, National Research Council - Via Moruzzi 1, 56124 Pisa, Italy, EU
2 Department of Information Engineering, University of Pisa - Via Diotisalvi 2, 56122 Pisa, Italy, EU
(a) Present address: Institute of Clinical Physiology, National Research Council - Via Moruzzi 1, 56124 Pisa, Italy, EU; email@example.com
Received: 9 October 2012
Accepted: 11 January 2013
Detrended cross-correlation analysis provides a scaling exponent that should characterize the power-law cross-correlation of two simultaneously recorded series. This exponent by itself is not able to guarantee the presence of cross-correlation, being strongly influenced by the auto-correlation properties of the single series. Through the use of σDCCA coefficients and simulation with ARFIMA models we built families of curves that can be used as templates to correctly detect the power-law behaviour and quantify the degree of coupling between series with any degree of auto-correlation.
PACS: 05.45.Tp – Time series analysis / 05.40.-a – Fluctuation phenomena, random processes, noise, and Brownian motion / 02.50.-r – Probability theory, stochastic processes, and statistics
© EPLA, 2013
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.