/UniBM

extreme value statistical analysis based on block maxima

Primary LanguageJupyter NotebookGNU Lesser General Public License v3.0LGPL-3.0

README

The Python scripts and the Jupyter Notebook (vignette.ipynb) in this repository are developed for extreme value statistical analysis.

Users are encouraged to refer to the accompanying paper for detailed method explanations and applications of these functions.

All bug reports and feature requests are welcomed.

The scripts are licensed under the GNU Lesser General Public License Version 3 (LGPL-3.0).

(# TODO: add proper paper citation)

unibm

cdf_func_kernel non parametric cdf estimator, by kernel smoothing

est_tail_dep_coeff pairwise tail dependence coefficient estimator

est_extremal_index_reciprocal extremal index (EI) estimator, by reciprocal of the mean of the block maxima;

viz_eir chart results from est_extremal_index_reciprocal(is_retn_vec=True)

est_extreme_value_index extreme value index (EVI) estimator, by MPMR & EMR

viz_evi_reg chart results from est_extreme_value_index(is_retn_vec=True)

Copyright (C) 2024- Tuoyuan Cheng, Kan Chen

UniBM is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

UniBM is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public License along with UniBM. If not, see http://www.gnu.org/licenses/.