VineCopulas: Difference between revisions
Created page with "{{MHRA |Publication Year=2024 |Access=Open |Link=https://joss.theoj.org/papers/10.21105/joss.06728 |Author(s)=Judith N. Claassen, Elco E. Koks, Marleen C. de Ruiter, Philip J. Ward, and Wiebke S. Jäger |Organisation(s)=Vrije Universiteit Amsterdam |Description=VineCopulas is a Python package for bivariate and vine copula modelling developed by Claassen et al. The package contains functionality to easily fit data to different copula families, generate random samples from..." |
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Latest revision as of 13:25, 9 April 2025
Author(s): Judith N. Claassen, Elco E. Koks, Marleen C. de Ruiter, Philip J. Ward, and Wiebke S. Jäger
Organisation(s)/Authors: Vrije Universiteit Amsterdam
Description:
VineCopulas is a Python package for bivariate and vine copula modelling developed by Claassen et al. The package contains functionality to easily fit data to different copula families, generate random samples from a (vine-) copula and also create conditional samples. The Python is pip downloadable (https://pypi.org/project/VineCopulas/), and has an extensive documentation (https://vinecopulas.readthedocs.io/en/latest/?badge=latest). Additionally, issues and recommendations to continuously improve and update the package can be suggested through GitHub (https://github.com/VU-IVM/VineCopulas).
Technical Considerations:
This package is coded in Python
Key Words:
Copulas, Statistics, Dependency
