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+r%22%22%22%0ATests for forecasting-related features not tested elsewhere%0A%22%22%22%0A%0Aimport numpy as np%0Aimport pandas as pd%0A%0Aimport pytest%0Afrom numpy.testing import assert_, assert_equal, assert_allclose%0A%0Afrom statsmodels.tsa.statespace import sarimax%0A%0A%0A@pytest.mark.parametrize('data', %5B'list', 'numpy', 'range', 'date', 'period'%5D)%0Adef test_append_multistep(data):%0A    # Test that %60MLEResults.append%60 works when called repeatedly%0A    endog = %5B1., 0.5, 1.5, 0.9, 0.2, 0.34%5D%0A    if data == 'numpy':%0A        endog = np.array(endog)%0A    elif data == 'range':%0A        endog = pd.Series(endog)%0A    elif data == 'date':%0A        index = pd.date_range(start='2000-01-01', periods=6, freq='MS')%0A        endog = pd.Series(endog, index=index)%0A    elif data == 'period':%0A        index = pd.period_range(start='2000-01', periods=6, freq='M')%0A        endog = pd.Series(endog, index=index)%0A%0A    # Base model fitting%0A    mod = sarimax.SARIMAX(endog%5B:2%5D, order=(1, 0, 0))%0A    res = mod.smooth(%5B0.5, 1.0%5D)%0A    assert_allclose(res.model.endog%5B:, 0%5D, %5B1., 0.5%5D)%0A    assert_allclose(res.forecast(1), 0.25)%0A%0A    # First append%0A    res1 = res.append(endog%5B2:3%5D)%0A    assert_allclose(res1.model.endog%5B:, 0%5D, %5B1., 0.5, 1.5%5D)%0A    assert_allclose(res1.forecast(1), 0.75)%0A%0A    # Second append%0A    res2 = res1.append(endog%5B3:5%5D)%0A    assert_allclose(res2.model.endog%5B:, 0%5D, %5B1., 0.5, 1.5, 0.9, 0.2%5D)%0A    assert_allclose(res2.forecast(1), 0.1)%0A%0A    # Third append%0A    res3 = res2.append(endog%5B5:6%5D)%0A    print(res3.model.endog)%0A    assert_allclose(res3.model.endog%5B:, 0%5D, %5B1., 0.5, 1.5, 0.9, 0.2, 0.34%5D)%0A    assert_allclose(res3.forecast(1), 0.17)%0A

Add test for multi-step append