Detrended Fluctuation Analysis (DFA) is a statistical method used to quantify the presence of long-range correlations in time series data. It assesses the self-similarity and fractal-like properties in a dataset by measuring the relationship between fluctuations at different time scales. DFA is commonly applied in various fields, including physiology, finance, and geophysics, to analyze complex time-dependent data.
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