docs: def copy(self):
          """
          Returns a copy of the distribution.
  
          Returns
          -------
          LinearGaussianCPD: copy of the distribution
  
          Examples
          --------
          >>> from pgmpy.factors.continuous import LinearGaussianCPD
          >>> cpd = LinearGaussianCPD('Y',  [0.2, -2, 3, 7], 9.6, ['X1', 'X2', 'X3'])
          >>> copy_cpd = cpd.copy()
          >>> copy_cpd.variable
          'Y'
          >>> copy_cpd.evidence
          ['X1', 'X2', 'X3']
          """
          copy_cpd = LinearGaussianCPD(self.variable, self.beta, self.variance,
                                       list(self.evidence))
  
          return copy_cpd