docs: def _lim_moment(self, u, order=1):
          """
          This method calculates the kth order limiting moment of
          the distribution. It is given by -
  
          E(u) = Integral (-inf to u) [ (x^k)*pdf(x) dx ] + (u^k)(1-cdf(u))
  
          where, pdf is the probability density function and cdf is the
          cumulative density function of the distribution.
  
          Reference
          ---------
          Klugman, S. A., Panjer, H. H. and Willmot, G. E.,
          Loss Models, From Data to Decisions, Fourth Edition,
          Wiley, definition 3.5 and equation 3.8.
  
          Parameters
          ----------
          u: float
              The point at which the moment is to be calculated.
  
          order: int
              The order of the moment, default is first order.
          """
          def fun(x):
              return np.power(x, order) * self.factor.pdf(x)
          return (integrate.quad(fun, -np.inf, u)[0] +
                  np.power(u, order)*(1 - self.factor.cdf(u)))