Documentation

Base

clayton.rng.base	A multivariate copula \(C : [0,1]^d \mapsto [0,1]\) of a d-dimensional random vector \(\mathbf{X}\) allows us to separate the effect of dependence from the effect of the marginal distributions such as:
clayton.rng.base.Multivariate([n_sample, dim])	Base class for multivariate copulas.
clayton.rng.base.Archimedean([theta, ...])	Base class for multivariate archimedean copulas.
clayton.rng.base.Extreme([n_sample, dim])	Base class for multivariate extreme value copulas.

Archimedean

clayton.rng.archimedean	Let \(\phi\) be a generator which is a strictly decreasing, convex function from \([0,1]\) to \([0,\infty]\) such that \(\phi(1)=0\) and \(\phi(1)=\infty\).
clayton.rng.archimedean.Amh([theta, ...])	Class for Amh copula model.
clayton.rng.archimedean.Clayton([theta, ...])	Class for Clayton copula.
clayton.rng.archimedean.Frank([theta, ...])	Class for Frank copula model.
clayton.rng.archimedean.Joe([theta, ...])	Class for Joe copula model.
clayton.rng.archimedean.Nelsen10([theta, ...])	Class for Nelsen10 copula model.
clayton.rng.archimedean.Nelsen11([theta, ...])	Class for Nelsen11 copula model.
clayton.rng.archimedean.Nelsen12([theta, ...])	Class for Nelsen12 copula model.
clayton.rng.archimedean.Nelsen13([theta, ...])	Class for Nelsen13 copula model.
clayton.rng.archimedean.Nelsen14([theta, ...])	Class for Nelsen14 copula model
clayton.rng.archimedean.Nelsen15([theta, ...])	Class for Nelsen15 copula model.
clayton.rng.archimedean.Nelsen22([theta, ...])	Class for Nelsen22 copula model.
clayton.rng.archimedean.Nelsen9([theta, ...])	Class for Nelsen9 copula model.

Extreme

clayton.rng.evd	Multivariate extreme value copula or, more generally, extreme value distribution are max-stable random vector with generalized extreme value margins and we may write
clayton.rng.evd.AsyMix([theta, psi1, ...])	Class for asymmetric mixed model.
clayton.rng.evd.AsyNegLog([theta, psi1, ...])	Class for asymmetric negative logistic copula model.
clayton.rng.evd.AsymmetricLogistic([theta, ...])	Class for multivariate asymmetric logistic copula model.
clayton.rng.evd.Bilog([theta, n_sample, dim])	Class for bilogistic distribution model Smith (1990).
clayton.rng.evd.HuslerReiss([sigmat, ...])	Class for Husler Reiss copula model.
clayton.rng.evd.Logistic([theta, n_sample, dim])	Class for multivariate Logistic copula model.
clayton.rng.evd.TEV([sigmat, psi1, ...])	Class for t extreme value model.