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Documentation:https://georgebv.github.io/pyextremes/

License:MIT

Support:ask a questionorcreate an issue,any input is appreciated and would help develop the project

pyextremes is a Python library aimed at performing univariateExtreme Value Analysis (EVA).It provides tools necessary to perform a wide range of tasks required toperform EVA, such as:

• extraction of extreme events from time series using methods such asBlock Maxima (BM) or Peaks Over Threshold (POT)
• fitting continuous distributions, such as GEVD, GPD, or user-specifiedcontinous distributions to the extracted extreme events
• visualization of model inputs, results, and goodness-of-fit statistics
• estimation of extreme events of given probability or return period(e.g. 100-year event) and of corresponding confidence intervals
• tools assisting with model selection and tuning, such as selection ofblock size in BM and threshold in POT

Check outthis repositorywith Jupyter notebooks used to produce figures for this readmeand for the official documentation.

Get latest version from PyPI:

pip install pyextremes

Install with optional dependencies:

pip install pyextremes[full]

Get latest experimental build from GitHub:

pip install"git+https://github.com/georgebv/pyextremes.git#egg=pyextremes"

Get pyextremes for the Anaconda Python distribution:

conda install -c conda-forge pyextremes

Model diagnostic

Extreme value extraction

Trace plot

Corner plot

I wanted to give kudos toJean Toilliez who has inspired me to develop this open-source project and who taught me a lot about the extreme value theory. Also big thanks to Max Larson who has introduced me to software development and statistics.