Evenly spacing in Detrended Fluctuation Analysis

• We analyze the effects of evenly spacing in Detrended Fluctuation Analysis (DFA).
• We compare evenly vs. logarithmic spacing with synthetic signals.
• Evenly spacing decreases by 36% the dispersion of estimates.
• Evenly spacing could allow the analysis of shorter time series.
• Evenly spacing should be systematically adopted in the application of DFA.

Detrended Fluctuation Analysis is a widely used method, which aims at assessing the level of self-similarity in time series. This method analyzes the diffusion properties of the signal, by computing the linear regression slope in the diffusion plot, representing in log–log coordinates the relationship between the variability of the signal and the length of the intervals over which this variability is computed. We compare in this paper the results obtained with logarithmically spaced and evenly spaced diffusion plots. The study shows the substantial benefits of evenly spacing, especially in the reduction of the variability of estimation.