def METHOD_NAME(m, m_err, v0, v0_err):
    """Computes error of trend estimate using gaussian error propagation
    The (normalised) trend is computed as T = m / v0
    where m denotes the slope of a regression line and v0 denotes the
    normalistation value. This method computes the uncertainty of T (delta_T)
    using gaussian error propagation of uncertainties accompanying m and v0.
    Parameters
    ----------
    m : float
        slope in units of <U> yr-1 (where <U> denotes the unit of the data).
        (m -> "montant").
    m_err : float
        slope error (same unit as `m`)
    v0 : float
        normalisation value in units of <U>
    v0_err : float
        error of `v0` (same units as `v0`)
    Returns
    -------
    float
        error of T in computed using gaussian error propagation of trend
        formula in units of %/yr
    """
    delta_sl = m_err / v0
    delta_ref = m * v0_err / v0**2
    return np.sqrt(delta_sl**2 + delta_ref**2) * 100