code: def link(self, mu, dist):
          
          return np.log(mu) - np.log(dist.levels - mu)
docs: glm link function
          this is useful for going from mu to the linear prediction
  
          Parameters
          ----------
          mu : array-like of legth n
          dist : Distribution instance
  
          Returns
          -------
          lp : np.array of length n