code: def beta(self):
          '''\
  The linear estimation of the parameter vector :math:`\beta` given by
  
  .. math::
  
      \beta = (X^T X)^-1 X^T y
          
  '''
          t = self.X.transpose()
          XX = dot(t,self.X)
          XY = dot(t,self.y)
          return linalg.solve(XX,XYf beta(self):
          '''\
  The linear estimation of the parameter vector :math:`\beta` given by
  
  .. math::
  
      \beta = (X^T X)^-1 X^T y
          
  '''
          t = self.X.transpose()
          XX = dot(t,self.X)
          XY = dot(t,self.y)
          return linalg.solve(XX,XY)
docs: \
  The linear estimation of the parameter vector :math:`\beta` given by
  
  .. math::
  
      \beta = (X^T X)^-1 X^T y