statsmodels.distributions.copula.api.IndependenceCopula

class statsmodels.distributions.copula.api.IndependenceCopula(k_dim=2)

Independence copula.

Copula with independent random variables.

\[C_ heta(u,v) = uv\]

Parameters:

k_dimint

Dimension, number of components in the multivariate random variable.

Methods

cdf(u[, args])	Cumulative distribution function evaluated at points u.
fit_corr_param(data)	Copula correlation parameter using Kendall's tau of sample data.
logpdf(u[, args])	Log of copula pdf, loglikelihood.
pdf(u[, args])	Probability density function of copula.
plot_pdf(*args)	Plot the PDF.
plot_scatter([sample, nobs, rng, ax])	Sample the copula and plot.
rvs([nobs, args, rng])	Generate random variates from the copula.
tau_simulated([nobs, rng])	Kendall's tau based on simulated samples.

tau

Notes

IndependenceCopula does not have copula parameters. If non-empty args are provided in methods, then a ValueError is raised. The args keyword is provided for a consistent interface across copulas.

Methods

cdf(u[, args])	Cumulative distribution function evaluated at points u.
fit_corr_param(data)	Copula correlation parameter using Kendall's tau of sample data.
logpdf(u[, args])	Log of copula pdf, loglikelihood.
pdf(u[, args])	Probability density function of copula.
plot_pdf(*args)	Plot the PDF.
plot_scatter([sample, nobs, rng, ax])	Sample the copula and plot.
rvs([nobs, args, rng])	Generate random variates from the copula.
tau()
tau_simulated([nobs, rng])	Kendall's tau based on simulated samples.