code: def calc_acceleration_abc(empirical_influence):
      
      influence_cubed = empirical_influence**3
      influence_squared = empirical_influence**2
      numerator = influence_cubed.sum(axis=0)
      denominator = 6 * (influence_squared.sum(axis=0))**1.5
      acceleration = numerator / denominator
      return acceleration
docs: Calculates the acceleration constant for 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
      -------
      acceleration : 1D ndarray.
          Contains the ABC confidence intervals' estimated acceleration vector.
  
      References
      ----------
      Efron, Bradley, and Robert J. Tibshirani. An Introduction to the Bootstrap.
          CRC press, 1994. Section 22.6, Equation 22.34.