def mquantiles_cimj(data, prob=[0.25,0.50,0.75], alpha=0.05, axis=None):
    """
    Computes the alpha confidence interval for the selected quantiles of the
    data, with Maritz-Jarrett estimators.

    Parameters
    ----------
    data : ndarray
        Data array.
    prob : sequence, optional
        Sequence of quantiles to compute.
    alpha : float, optional
        Confidence level of the intervals.
    axis : int or None, optional
        Axis along which to compute the quantiles.
        If None, use a flattened array.

    """
    alpha = min(alpha, 1-alpha)
    z = norm.ppf(1-alpha/2.)
    xq = mstats.mquantiles(data, prob, alphap=0, betap=0, axis=axis)
    smj = mjci(data, prob, axis=axis)
    return (z * smj - xq, xq + z * smj)
dataset/ETHPy150Open scipy/scipy/scipy/stats/mstats_extras.py/mquantiles_cimj/swapped operands of `-`