class_docstr: Class for Multivariate Normal Distribution
  
  uses Cholesky decomposition of covariance matrix for the transformation
  of the data
class_docstr_tok: ["Class","for","Multivariate","Normal","Distribution","uses","Cholesky","decomposition","of","covariance","matrix","for","the","transformation","of","the","data"]
docstr: random variable
  
  Parameters
  ----------
  size : int or tuple
      the number and shape of random variables to draw.
  
  Returns
  -------
  rvs : ndarray
      the returned random variables with shape given by size and the
      dimension of the multivariate random vector as additional last
      dimension
  
  Notes
  -----
  uses numpy.random.multivariate_normal directly
code: def rvs(self, size=1):
      """random variable
  
      Parameters
      ----------
      size : int or tuple
          the number and shape of random variables to draw.
  
      Returns
      -------
      rvs : ndarray
          the returned random variables with shape given by size and the
          dimension of the multivariate random vector as additional last
          dimension
  
      Notes
      -----
      uses numpy.random.multivariate_normal directly
  
      """
      return np.random.multivariate_normal(
          self.mean, self.sigma, size=size
      )
  
imports: import numpy
  from scipy import special
  from statsmodels.sandbox.distributions.multivariate import mvstdtprob
  from .extras import mvnormcdf
label_desc: Use image node_id 1 for calling the MVNormal obj's underlying member method code with example usage: obj.rvs(size) and returns: np