statsmodels.distributions.copula.api.ClaytonCopula

class statsmodels.distributions.copula.api.ClaytonCopula(theta=None, k_dim=2)[source]

Clayton copula.

Dependence is greater in the negative tail than in the positive.

\[C_\theta(u,v) = \left[ \max\left\{ u^{-\theta} + v^{-\theta} -1 ; 0 \right\} \right]^{-1/\theta}\]

with \(\theta\in[-1,\infty)\backslash\{0\}\).

Methods

cdf(u[, args])

Evaluate cdf of Archimedean copula.

fit_corr_param(data)

Copula correlation parameter using Kendall’s tau of sample data.

logpdf(u[, args])

Evaluate log pdf of multivariate Archimedean copula.

pdf(u[, args])

Evaluate pdf of Archimedean copula.

plot_pdf([ticks_nbr, ax])

Plot the PDF.

plot_scatter([sample, nobs, random_state, ax])

Sample the copula and plot.

rvs([nobs, args, random_state])

Draw n in the half-open interval [0, 1).

tau([theta])

tau_simulated([nobs, random_state])

Kendall’s tau based on simulated samples.

theta_from_tau(tau)