pycop: a Python package for dependence modeling with copulas

The purpose of the package is to provide tools for copula modeling with Python. It provides all of the common parametric copula functions to model a variety of dependence structures. The package includes features such as Elliptical copulas (Gaussian & Student), common Archimedean copula functions, mixture models defined as convex combinations of copulas, random sample generation models, empirical copula methods, and the computation of parametric and nonparametric estimation of tail dependence coefficients. The pycop package is built on a user-friendly API to create a specific copula object for which we can estimate the parameters for a given dataset, generate random samples and plot the density and cumulative distribution functions. The library comes with documentation and several Jupyter notebook examples