statsmodels.distributions.copula.api.GaussianCopula.plot_scatter¶

GaussianCopula.plot_scatter(sample=None, nobs=500, random_state=None, ax=None)¶

Sample the copula and plot.

Parameters:¶

samplearray_like, optional: The sample to plot. If not provided (the default), a sample is generated.
nobsint, optional: Number of samples to generate from 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.
axAxesSubplot, optional: If given, this subplot is used to plot in instead of a new figure being created.

Returns:¶

figFigure: If ax is None, the created figure. Otherwise the figure to which ax is connected.
samplearray_like (n, d): Sample from the copula.