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A Python package for copula analysis and computation.

Project description

copul

copul is a package designed for mathematical computation with and visualization of bivariate copula families.

Install

Install the copul library using pip.

pip install copul

Documentation

A guide and documentation is available at https://copul.readthedocs.io/.

Copula families and copulas

The copul package covers implementations of the following copula families:

  • Archimedean copula families: The 22 Archimedean copula families from the book "Nelsen - An Introduction to Copulas" including
    • Clayton
    • Gumbel-Hougaard
    • Frank
    • Joe
    • Ali-Mikhail-Haq
    • etc.
  • Extreme-value copulas families:
    • BB5
    • Cuadras-Augé
    • Galambos
    • Gumbel
    • Husler-Reiss
    • Joe
    • Marshall-Olkin
    • tEV
    • Tawn
  • Elliptical copula families:
    • Gaussian
    • Student's t
    • Laplace.
  • Other copula families:
    • Farlie-Gumbel-Morgenstern
    • Fréchet
    • Mardia
    • Plackett
    • Raftery

Furthermore, the package provides the following copulas:

  • Independence copula
  • Lower and upper Fréchet bounds
  • Checkerboard copulas

Copula properties

The following properties are available for the above copula families and copulas if they exist and are known:

  • cdf: Cumulative distribution function
  • pdf: Probability density function
  • cond_distr_1, cond_distr_2: Conditional distribution functions
  • lambda_L, lambda_U: Lower and upper tail dependence coefficients
  • rho, tau, xi: Spearman's rho, Kendall's tau, and Chatterjee's xi
  • generator, inv_generator: Generator and inverse generator for Archimedean copula families
  • pickands: Pickands dependence functions for extreme-value copula families

Copula methods

The following methods are available for the above copula families and copulas:

  • rvs: Generate random samples from the copula
  • scatter_plot: Generate a scatter plot of the copula
  • plot_cdf: Visualize the cumulative distribution function
  • plot_pdf: Visualize the probability density function
  • plot_rank_correlations: Visualize Spearman's rho, Kendall's tau, and Chatterjee's xi
  • plot_generator: Visualize the generator function
  • plot_pickands: Visualize the Pickands dependence function

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