def noise_covariance(fit, dof=2, **kw):
    """
    Covariance taking into account the 'noise covariance' of the data.
    This is technically more realistic for continuously sampled data.
    From Faber, 1993
    """
    ev = fit.eigenvalues
    measurement_noise = ev[-1] / (fit.n - dof)
    return 4 * ev * measurement_noise
