code: def deviance(self, y, mu, scaled=True):
          
          dev = (y - mu)**2
          if scaled:
              dev /= self.scale
          return dev
docs: model deviance
  
          for a gaussian linear model, this is equal to the SSE
  
          Parameters
          ----------
          y : array-like of length n
              target values
          mu : array-like of length n
              expected values
          scaled : boolean, default: True
              whether to divide the deviance by the distribution scaled
  
          Returns
          -------
          deviances : np.array of length n