Tsallis entropy - advice needed regarding obtaining probability distribution

As is always the way I stumbled across Tsallis entropy on SO whilst looking for something completely different. This soon lead me reading all sorts of interesting but terse academic papers.

I am unfortunately a mere layman and I still have one big unsolved question.

The key input to Tsallis entropy is a probability array.

What I don't understand is how do you get it out of a time-series ?

Allow me to give you a completely hypothetical example:

  • I have a database with 10 year's worth of non-stationary data e.g. house prices,wind speeds, vehicle speeds etc.
  • I want to explore it on various time frames (e.g. daily, monthly etc.)
  • So conceptually I run through the 10 years of data with rolling-window of chosen delta to generate features, one of which will be a Tsallis value.
  • What happens about feeding into Tsallis ? The individual numbers won't be of use ? log-diffs won't be of much use ? Where does this mythical array of probabilities come from ?

Topic feature-engineering feature-construction time-series

Category Data Science

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