def METHOD_NAME():
    endog = y[:100]
    cv = RollingForecastCV(initial=90, step=1, h=4)
    gen = cv.split(endog)
    expected = [
        (np.arange(0, 90), np.array([90, 91, 92, 93])),
        (np.arange(0, 91), np.array([91, 92, 93, 94])),
        (np.arange(0, 92), np.array([92, 93, 94, 95])),
        (np.arange(0, 93), np.array([93, 94, 95, 96])),
        (np.arange(0, 94), np.array([94, 95, 96, 97])),
        (np.arange(0, 95), np.array([95, 96, 97, 98])),
        (np.arange(0, 96), np.array([96, 97, 98, 99])),
    ]
    # should be 7
    for i, (train, test) in enumerate(gen):
        assert_array_equal(train, expected[i][0])
        assert_array_equal(test, expected[i][1])
    # assert no extra splits
    with pytest.raises(StopIteration):
        next(gen)