def METHOD_NAME(sunspots, not_implemented):
    class DummyPred:
        def __init__(self, predicted_mean, row_labels):
            self.predicted_mean = predicted_mean
            self.row_labels = row_labels
            def f():
                raise NotImplementedError
            if not_implemented:
                self.forecast = property(f)
    class DummyRes:
        def __init__(self, res):
            self._res = res
        def forecast(self, *args, **kwargs):
            return self._res.forecast(*args, **kwargs)
        def get_prediction(self, *args, **kwargs):
            pred = self._res.get_prediction(*args, **kwargs)
            return DummyPred(pred.predicted_mean, pred.row_labels)
    class DummyMod:
        def __init__(self, y):
            self._mod = ARIMA(y)
        def fit(self, *args, **kwargs):
            res = self._mod.fit(*args, **kwargs)
            return DummyRes(res)
    stl_mod = STLForecast(sunspots, model=DummyMod, period=11)
    stl_res = stl_mod.fit()
    with pytest.warns(UserWarning, match="The variance of"):
        pred = stl_res.get_prediction()
    assert np.all(np.isnan(pred.var_pred_mean))