statsmodels.distributions.mixture_rvs.MixtureDistribution.rvs#

MixtureDistribution.rvs(prob, size, dist, kwargs=None, rng=None)[source]#

Sample from a mixture of distributions.

Parameters:

probarray_like: Probability of sampling from each distribution in dist
sizeint: The length of the returned sample.
distarray_like: An iterable of distributions objects from scipy.stats.
kwargstuple of dicts, optional: A tuple of dicts. Each dict in kwargs can have keys loc, scale, and args to be passed to the respective distribution in dist. If not provided, the distribution defaults are used.
rngint, array_like of int, numpy.random.Generator, or numpy.random.RandomState, optional: If rng is None, the legacy global (singleton) RandomState provided by numpy.random is used; this behavior is deprecated and will change to creating a new Generator using fresh entropy from the operating system in a future release. If rng is an int or array of ints, a new RandomState instance is created, seeded with rng. If rng is already a Generator or RandomState instance, that instance is used.
rngint, array_like of int, numpy.random.Generator, or numpy.random.RandomState, optional: Deprecated since version 0.15: random_state has been deprecated. In-line with SPEC-007, use rng for passing a random number generator or seed.

Returns: