class_docstr: Base Class for multivariate elliptical distributions, normal and t
  
  contains common initialization, and some common methods
  subclass needs to implement at least rvs and logpdf methods
class_docstr_tok: ["Base","Class","for","multivariate","elliptical","distributions",",","normal","and","t","contains","common","initialization",",","and","some","common","methods","subclass","needs","to","implement","at","least","rvs","and","logpdf","methods"]
docstr: probability density function
  
  Parameters
  ----------
  x : array_like
      can be 1d or 2d, if 2d, then each row is taken as independent
      multivariate random vector
  
  Returns
  -------
  pdf : float or array
      probability density value of each random vector
code: def pdf(self, x):
      """probability density function
  
      Parameters
      ----------
      x : array_like
          can be 1d or 2d, if 2d, then each row is taken as independent
          multivariate random vector
  
      Returns
      -------
      pdf : float or array
          probability density value of each random vector
  
      """
      return np.exp(self.logpdf(x))
  
imports: import numpy
  from scipy import special
  from statsmodels.sandbox.distributions.multivariate import mvstdtprob
  from .extras import mvnormcdf
label_desc: Use image node_id 7 for calling the MVElliptical obj's underlying member method code with example usage: obj.pdf(x) and returns: np