docs: def initialize(self, endog, freq_weights):
          '''
          Initialize the response variable.
  
          Parameters
          ----------
          endog : array
              Endogenous response variable
  
          Returns
          --------
          If `endog` is binary, returns `endog`
  
          If `endog` is a 2d array, then the input is assumed to be in the format
          (successes, failures) and
          successes/(success + failures) is returned.  And n is set to
          successes + failures.
          '''
          # if not np.all(np.asarray(freq_weights) == 1):
          #     self.variance = V.Binomial(n=freq_weights)
          if (endog.ndim > 1 and endog.shape[1] > 1):
              y = endog[:, 0]
              # overwrite self.freq_weights for deviance below
              self.n = endog.sum(1)
              return y*1./self.n, self.n
          else:
              return endog, np.ones(endog.shape[0])