`scipy.stats._multivariate:multivariate_hypergeom_gen.rvs`

source: /scipy/stats/_multivariate.py :5998

Signature

def rvs ( self , m , n , size = None , random_state = None )

Summary

Draw random samples from a multivariate hypergeometric distribution.

Parameters

m : array_like: The number of each type of object in the population. That is, $m [i]$ is the number of objects of type $i$ .
n : array_like: The number of samples taken from the population.
size : integer or iterable of integers, optional: Number of samples to draw. Default is None, in which case a single variate is returned as an array with shape m.shape.
seed : {None, int, np.random.RandomState, np.random.Generator}, optional: Used for drawing random variates. If seed is None, the ~np.random.RandomState singleton is used. If seed is an int, a new RandomState instance is used, seeded with seed. If seed is already a RandomState or Generator instance, then that object is used. Default is None.

Returns

rvs : array_like: Random variates of shape size or m.shape (if size=None).

Notes

m must be an array of positive integers. If the quantile $i$ contains values out of the range $[0, m_{i}]$ where $m_{i}$ is the number of objects of type $i$ in the population or if the parameters are inconsistent with one another (e.g. x.sum() != n), methods return the appropriate value (e.g. 0 for pmf). If m or n contain negative values, the result will contain nan there.

Also note that NumPy's multivariate_hypergeometric sampler is not used as it doesn't support broadcasting.

Aliases

scipy.stats._multivariate.multivariate_hypergeom_gen.rvs