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Detrended Flucatuation Analysis (DFA) of Long-range temporal correlations

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The DFA algorithm is a scaling analysis method used to estimate long-range temporal correlations.

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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

Comments and Ratings (2)

ali zare

Laya Das

How can one obtain the distribution of the scaling exponent? How to obtain the standard deviation of the estimates?

Updates

1.1

I corrected a missing 'd' in the title

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