`scipy.stats._multivariate:multivariate_t_frozen.cdf`

Signature

def cdf(self, x, *, maxpts = None, lower_limit = None, random_state = None)

Multivariate t-distribution cumulative distribution function.

x : array_like: Points at which to evaluate the cumulative distribution function.
maxpts : int, optional: Maximum number of points to use for integration. The default is 1000 times the number of dimensions.
lower_limit : array_like, optional: Lower limit of integration of the cumulative distribution function. Default is negative infinity. Must be broadcastable with x.
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.

cdf : ndarray or scalar: Cumulative distribution function evaluated at x.

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

✓

multivariate_t.cdf(x, loc, shape, df)

✗

np.float64(0.6482055219097868)