  We present a modification to the diffusion entropy analysis method for
detecting temporal scaling. Diffusion entropy analysis detects temporal scaling
in a data set by converting a time-series into a diffusion trajectory and using
the entropy of that trajectory to measure the temporal scaling in the data. We
modify this by performing an event detection step to construct the diffusion
trajectory. The new modified diffusion entropy analysis offers substantial
improvements over the original method, especially for noisy data. We describe
the method's purpose, how it works step-by-step, its application, and future
development.
