def calc_std_error_abc(empirical_influence):
    """
    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.
    """
    num_obs = empirical_influence.shape[0]
    std_error = ((empirical_influence**2).sum(axis=0))**0.5 / num_obs
    return std_error
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.