def _compute_sigmah(obj, h):
    """
    Computes the sigmah requiered for prediction intervals
    """
    var_mult = np.zeros(h)
    var_mult[0] = 1
    if h > 1:
        for j in range(1, h):
            if j == 1:
                f_running = np.eye(obj["F"].shape[1])
            else:
                f_running = np.dot(f_running, obj["F"])
            cj = np.dot(np.dot(obj["w_transpose"][0], f_running), obj["g"][:, 0])
            var_mult[j] = var_mult[j - 1] + cj**2
    sigma2h = obj["sigma2"] * var_mult
    sigmah = np.sqrt(sigma2h)
    return sigmah

    Computes the sigmah requiered for prediction intervals
    
python/statsforecast/tbats.py