Using detrended fluctuation analysis for lagged correlation analysis of nonstationary signals.

Here we propose a method, based on detrended fluctuation analysis (DFA), to investigate lagged correlations for nonstationary time series. The aim is to show that the largest correlation can be found at positive lags, reflecting the existence of underlying delays in the evolution of real time sequences. The performance of the lagged DFA method is illustrated by selected real examples.

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