copul 0.0.11

Mathematical computation and visualization of bivariate copulas.

copul

Copula properties

For any of the bivariate copula families specified below, e.g. copula = copul.Galambos(), get the following properties:

• Cumulative distribution function via copula.cdf
• Density function via copula.pdf
• Conditional distribution function via copula.cond_distr_1 and copula.cond_distr_2

Supported copula families:

Archimedean Copulas

The 22 Archimedean copula families from the book "Nelsen - An Introduction to Copulas", accessible via copul.archimedean.Nelsen1, copul.archimedean.Nelsen2, etc. Let copula be any instance of those classes, e.g. copula = copul.archimedean.Nelsen1().

For these families, the following properties are available:

• generator function is available via e.g. copula.generator
• inverse generator function is available via e.g. copula.inverse_generator
• CI char function is available via e.g. copula.ci_char
• the MTP2 char function is available via e.g. copula.mtp2_char

Extreme Value Copulas

• BB5
• Cuadras-Augé
• Galambos
• Gumbel
• Husler-Reiss
• Joe
• Marshall-Olkin
• tEV
• tawn

Let copula be any instance of those classes, e.g. copula = copul.extreme_value.Galambos(). Then, the Pickands function is available via e.g. copula.pickands.

Other

• Farlie-Gumbel-Morgenstern
• Fréchet
• Mardia
• Plackett
• Raftery

Sample Usage

import copul

galambos = copul.extreme_value.Galambos()
params = galambos.sample_parameters(3)
galambos.plot_pickands(params)

clayton = copul.archimedean.Clayton()
clayton(theta=1.5).plot_cdf()
clayton(theta=2.5).plot_pdf()