Detrended Fluctuation Analysis (DFA)

F(n) ~ nᵅ — detecting long-range correlations in non-stationary signals

Signal Parameters

Estimated α (DFA):
True H:
Class:
Variance:
DFA algorithm: 1) Integrate signal, 2) divide into windows of size n, 3) detrend each window (polynomial fit), 4) compute RMS fluctuation F(n), 5) fit F(n)~nᵅ.

α=0.5: white noise. α=1: 1/f (pink). α=1.5: Brownian. α>0.5: persistent. α<0.5: anti-persistent.