In stochastic processes, chaos theory and time series analysis, detrended fluctuation analysis (DFA) is a method for determining the statistical selfaffinity of a signal by computing alpha (or Hurst exponent H).It is useful for analysing time series that appear to be longrange dependent processes. However, the conventional DFA only scale the second order statistical moment and assumes that the process are normal distributed. MFDFA1 and MFDFA2 in the present zipfolder computes the H(q) for all qorder statistical moments as well as the local Hurst exponent H(t). Furthermore, H(q) and H(t) are also used to compute the multifractal spectrum D(h) by a legendre transform of H(q) or directly from the histogram of H(t).
If the codes are used in scientific publications please cite Ihlen (2012) contained in the zipfolder.
Modifications of MFDFA code with wavelet and EMD detrending are availible at www.ntnu.edu/inm/geri/software
