3.3.4.2.1.1.1. statsmodels.distributions.mixture_rvs.MixtureDistribution.cdf

MixtureDistribution.cdf(x, prob, dist, kwargs=None)

cdf of a mixture of distributions.

Parameters:

prob : array-like

Probability of sampling from each distribution in dist

size : int

The length of the returned sample.

dist : array-like

An iterable of distributions objects from scipy.stats.

kwargs : tuple 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.

Examples

Say we want 5000 random variables from mixture of normals with two distributions norm(-1,.5) and norm(1,.5) and we want to sample from the first with probability .75 and the second with probability .25.

>>> from scipy import stats
>>> prob = [.75,.25]
>>> Y = mixture.pdf(x, prob, dist=[stats.norm, stats.norm], kwargs =
            (dict(loc=-1,scale=.5),dict(loc=1,scale=.5)))