`scipy.stats._multivariate:multivariate_t_gen.rvs`

Signature

def rvs(self, loc = None, shape = 1, df = 1, size = 1, random_state = None)

Draw random samples from a multivariate t-distribution.

loc : array_like, optional: Location of the distribution. (default 0)
shape : array_like, optional: Positive semidefinite matrix of the distribution. (default 1)
df : float, optional: Degrees of freedom of the distribution; must be greater than zero. If np.inf then results are multivariate normal. The default is 1.
allow_singular : bool, optional: Whether to allow a singular matrix. (default False)
size : int, optional: Number of samples to draw (default 1).
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.

rvs : ndarray or scalar: Random variates of size (size, P), where P is the dimension of the random variable.

from scipy.stats import multivariate_t
x = [0.4, 5]
loc = [0, 1]
shape = [[1, 0.1], [0.1, 1]]
df = 7

✓

multivariate_t.rvs(loc, shape, df)

✗

array([-1.12377,  3.90762])