Detrended Flucatuation Analysis (DFA) of Long-range temporal correlations
The DFA algorithm is a scaling analysis method used to estimate long-range temporal correlations.
You are now following this Submission
- You will see updates in your followed content feed
- You may receive emails, depending on your communication preferences
The DFA algorithm is a scaling analysis method used to estimate long-range temporal correlations.
Description: The Detrended flctuation analsysis (DFA) algorithm is a scaling analysis method used to estimate long-range temporal correlations of power-law form. In other words, if a sequence of events has a non-random temporal structure with slowly decaying auto-correlations, DFA can quantify how slowly these correlations decay as indexed by the DFA power-law exponent.
We here present the DFA algorithm implemented as a Biomarker for the Neurophysiological Biomarker Toolbox. You can download this toolbox at http://www.nbtwiki.net.
A tutorial on Detrended fluctuation analysis can be found here: http://www.nbtwiki.net/doku.php?id=tutorial:detrended_fluctuation_analysis_dfa
Cite As
Simon-Shlomo Poil (2026). Detrended Flucatuation Analysis (DFA) of Long-range temporal correlations (https://www.mathworks.com/matlabcentral/fileexchange/40011-detrended-flucatuation-analysis-dfa-of-long-range-temporal-correlations), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.1.0.0 (6.89 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
