Diffusion Entropy Analysis is a time-series analysis method for detecting temporal scaling in a data set, such as particle motion, a seismograph, or an electroencephalograph signal. Diffusion Entropy Analysis converts a timeseries into a diffusion trajectory and uses the entropy of this trajectory to measure the temporal scaling in the data. This is accomplished by moving a window along the trajectory, then using the relationship between the natural logarithm of the length of the window and the Shannon entropy to extract the scaling of the time-series process.
For further details about the method and how it works, please see Culbreth, G., Baxley, J. and Lambert, D., 2023. Detecting temporal scaling with modified diffusion entropy analysis. arXiv preprint arXiv:2311.11453.
The pymdea package is available on pypi and can be installed with pip:
pip install pymdeapymdea can also be installed with uv
uv add pymdeaA user guide is available in the documentation.
