statsmodels.distributions.copula.api.GaussianCopula.rvs

GaussianCopula.rvs(nobs=1, args=(), random_state=None)

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

Marginals are uniformly distributed.

Parameters:

nobsint, optional

Number of samples to generate from the copula. Default is 1.

argstuple

Arguments for copula parameters. The number of arguments depends on the copula.

random_state{None, int, numpy.random.Generator}, optional

If seed is None then the legacy singleton NumPy generator. This will change after 0.13 to use a fresh NumPy Generator, so you should explicitly pass a seeded Generator if you need reproducible results. If seed is an int, a new Generator instance is used, seeded with seed. If seed is already a Generator instance then that instance is used.

Returns:

samplearray_like (nobs, d)

Sample from the copula.

See also

statsmodels.tools.rng_qrng.check_random_state