statsmodels.distributions.copula.api.rvs_kernel

statsmodels.distributions.copula.api.rvs_kernel(sample, size, bw=1, k_func=None, return_extras=False, rng=None)

Random sampling from empirical copula using Beta distribution

Parameters:

samplendarray

Sample of multivariate observations in (0, 1) interval.

sizeint

Number of observations to simulate.

bwfloat, optional

Bandwidth for Beta sampling. The beta copula corresponds to a kernel estimate of the distribution. bw=1 corresponds to the empirical beta copula. A small bandwidth like bw=0.001 corresponds to small noise added to the empirical distribution. Larger bw, e.g., bw=10 corresponds to kernel estimate with more smoothing.

k_funccallable, optional

The default kernel function is currently a beta function with 1 added to the first beta parameter.

return_extrasbool, optional

If this is False, then only the random sample will be returned. If true, then extra information is returned that is mainly of interest for verification.

rngint, array_like of int, numpy.random.Generator, or numpy.random.RandomState, optional

If rng is None, a new Generator is created using fresh entropy from the operating system. If rng is an int or array of ints, a new Generator is created, seeded with rng. If rng is already a Generator or RandomState instance, that instance is used.

Returns:

rvsndarray

Multivariate sample with size observations drawn from the Beta Copula.

Notes

Status: experimental, API will change.