'Create a frozen multivariate normal distribution.
Parameters
mean : array_like, optional
Mean of the distribution (default zero)
cov : array_like, optional
Covariance matrix of the distribution (default one)
Examples
When called with the default parameters, this will create a 1D random
variable with mean 0 and covariance 1:
>>> from scipy.stats import multivariate_normal
>>> r = multivariate_normal()
>>> r.mean
array([ 0.])
>>> r.cov
array([[1.]])'

def __init__(self, mean=None, cov=1):

    (self.dim, self.mean, self.cov) = _process_parameters(None, mean, cov)
    (self.prec_U, self._log_det_cov) = _psd_pinv_decomposed_log_pdet(self.cov)
    self._mnorm = multivariate_normal_gen()
