3.3.4.1.2. statsmodels.distributions.mixture_rvs.mv_mixture_rvs

statsmodels.distributions.mixture_rvs.mv_mixture_rvs(prob, size, dist, nvars, **kwargs)

Sample from a mixture of multivariate 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 instances with callable method rvs.

nvargs : int

dimension of the multivariate distribution, could be inferred instead

kwargs : tuple of dicts, optional

ignored

Examples

Say we want 2000 random variables from mixture of normals with two multivariate normal distributions, and we want to sample from the first with probability .4 and the second with probability .6.

import statsmodels.sandbox.distributions.mv_normal as mvd

cov3 = np.array([[ 1. , 0.5 , 0.75],

[ 0.5 , 1.5 , 0.6 ], [ 0.75, 0.6 , 2. ]])

mu = np.array([-1, 0.0, 2.0]) mu2 = np.array([4, 2.0, 2.0]) mvn3 = mvd.MVNormal(mu, cov3) mvn32 = mvd.MVNormal(mu2, cov3/2., 4) rvs = mix.mv_mixture_rvs([0.4, 0.6], 2000, [mvn3, mvn32], 3)