code: def calc_std_error_abc(empirical_influence):
      
      num_obs = empirical_influence.shape[0]
      std_error = ((empirical_influence**2).sum(axis=0))**0.5 / num_obs
      return std_error
docs: Calculates the standard error of the MLE estimates for use in calculating
      the approximate bootstrap confidence (ABC) intervals.
  
      Parameters
      ----------
      empirical_influence : 2D ndarray.
          Should have one row for each observation. Should have one column for
          each parameter in the parameter vector being estimated. Elements should
          denote the empirical influence of the associated observation on the
          associated parameter.
  
      Returns
      -------
      std_error : 1D ndarray.
          Contains the standard error of the MLE estimates for use in the ABC
          confidence intervals.
  
      References
      ----------
      Efron, Bradley, and Robert J. Tibshirani. An Introduction to the Bootstrap.
          CRC press, 1994. Section 22.6, Equation 22.31.