clayton.rng.base.Multivariate

class clayton.rng.base.Multivariate(n_sample=1, dim=2)

Base class for multivariate copulas. This class allows to instantiate all its subclasses and serves as a unique entry point for the multivariate copulas classes.

Raises:

ValueError:

wrong sample size.

ValueError:

wrong dimension.

ValueError:

inv_cdf should be a list.

ValueError:

wrong dimension of inv_cdf.

Returns:

clayton.rng.base.Multivariate

abstract __init__(n_sample=1, dim=2)

Initialize Multivariate object.

Args:

n_sample (int, optional):

sample size. Defaults to 1.

dim (int, optional):

dimension. Defaults to 2.

Raises:

ValueError:

sample size is not a positive integer.

ValueError:

dimension is not a positive integer.

Methods

__init__([n_sample, dim])	Initialize Multivariate object.
sample(inv_cdf)	Draws a bivariate sample the desired copula and invert it by a given generalized inverse of cumulative distribution function.
sample_unimargin()	see the corresponding documentation in lower subclasses.