A program and module that use a sstatistical analysis technique for time series(Rescaled Range), which aims to find the Hurst exponent: https://en.wikipedia.org/wiki/Rescaled_range

Calculates the generalized Hurst exponent of a time series. The Hurst exponent gives a value indicating the long-term memory of a time-series, similar to the decay of a autocorrelation function: https://en.wikipedia.org/wiki/Hurst_exponent

init.py series [exponent]

positional arguments:

• series : A list with all data in floats/ints

optional arguments:

• exponent : Determine the range of the analysis, based on exponents of the number 2, so if 1 is passed then will be calculated the range 1/2, if 2 it will be calculated for 1/2 and 1/4,if 3 for 1/2, 1/4 and 1/8, and so on. If nothing is passed, will be calculate to the more accurate range

Please use the issue tracker to report any bugs or file feature requests.

1. Create an issue to discuss about your idea
2. [Fork it] (https://github.com/francnascimento/RescaledRange/fork)
3. Create your feature branch (git checkout -b my-new-feature)
4. Commit your changes (git commit -am 'Add some feature')
5. Push to the branch (git push origin my-new-feature)
6. Create a new Pull Request
7. Profit! ✅

This project is free to use according to the MIT License as long as you cite me and the License (read the License for more details). You can cite me by pointing to the following link:

• https://github.com/francnascimento/rescaled-range