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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 (3)

Eric You

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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