def test_autoreg_append_deterministic(append_data):
y = append_data.y
y_oos = append_data.y_oos
y_both = append_data.y_both
x = append_data.x
x_oos = append_data.x_oos
x_both = append_data.x_both
terms = [TimeTrend(constant=True, order=1), Seasonality(12)]
dp = DeterministicProcess(y.index, additional_terms=terms)
res = AutoReg(y, lags=3, trend="n", deterministic=dp).fit()
res_append = res.append(y_oos, refit=True)
res_direct = AutoReg(y_both,
lags=3,
trend="n",
deterministic=dp.apply(y_both.index)).fit()
assert_allclose(res_append.params, res_direct.params)
res_np = AutoReg(np.asarray(y), lags=3, trend="n", deterministic=dp).fit()
res_append_np = res_np.append(np.asarray(y_oos))
assert_allclose(res_np.params, res_append_np.params)
res = AutoReg(y, exog=x, lags=3, trend="n", deterministic=dp).fit()
res_append = res.append(y_oos, exog=x_oos, refit=True)
res_direct = AutoReg(
y_both,
exog=x_both,
lags=3,
trend="n",
deterministic=dp.apply(y_both.index),
).fit()
assert_allclose(res_append.params, res_direct.params)
def test_autoreg_append(append_data, use_pandas, lags, trend, seasonal):
period = 12 if not use_pandas else None
y = append_data.y
y_oos = append_data.y_oos
y_both = append_data.y_both
x = append_data.x
x_oos = append_data.x_oos
x_both = append_data.x_both
if not use_pandas:
y = np.asarray(y)
x = np.asarray(x)
y_oos = np.asarray(y_oos)
x_oos = np.asarray(x_oos)
y_both = np.asarray(y_both)
x_both = np.asarray(x_both)
res = AutoReg(y, lags=lags, trend=trend, seasonal=seasonal,
period=period).fit()
res_append = res.append(y_oos, refit=True)
res_direct = AutoReg(y_both,
lags=lags,
trend=trend,
seasonal=seasonal,
period=period).fit()
res_exog = AutoReg(y,
exog=x,
lags=lags,
trend=trend,
seasonal=seasonal,
period=period).fit()
res_exog_append = res_exog.append(y_oos, exog=x_oos, refit=True)
res_exog_direct = AutoReg(
y_both,
exog=x_both,
lags=lags,
trend=trend,
seasonal=seasonal,
period=period,
).fit()
assert_allclose(res_direct.params, res_append.params)
assert_allclose(res_exog_direct.params, res_exog_append.params)
if use_pandas:
with pytest.raises(TypeError, match="endog must have the same type"):
res.append(np.asarray(y_oos))
with pytest.raises(TypeError, match="exog must have the same type"):
res_exog.append(y_oos, np.asarray(x_oos))
with pytest.raises(ValueError, match="Original model does"):
res.append(y_oos, exog=x_oos)
with pytest.raises(ValueError, match="Original model has exog"):
res_exog.append(y_oos)
