pyextremes 2.2.0

Extreme Value Analysis (EVA) in Python

pyextremes

Extreme Value Analysis (EVA) in Python

About

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

License: MIT

E-Mail: [e-mail]

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

• extraction of extreme events from time series using methods such as Block Maxima (BM) or Peaks Over Threshold (POT)
• fitting continuous distributions, such as GEVD, GPD, or user-specified continous 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 of block size in BM and threshold in POT

Installation

Get latest version from PyPI:

pip install pyextremes

Get latest experimental build from GitHub:

pip install git+https://github.com/georgebv/pyextremes

Get pyextremes for the Anaconda Python distribution:

conda install -c conda-forge pyextremes

Tutorials

This section will be removed in the future in favor of the official documentation which can be found at https://georgebv.github.io/pyextremes/.

• Basic usage
• Threshold selection

Illustrations

Model diagnostic

Extreme value extraction

Trace plot

Corner plot