Comments (2)
I'll take a look when I get a chance. PRs are always welcome.
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This should be handled now in v0.8.1. I've even got a test for this exact case (pyramid/arima/tests/test_arima:test_issue_30)
:
def test_issue_30():
# From the issue:
vec = np.array([33., 44., 58., 49., 46., 98., 97.])
auto_arima(vec, out_of_sample_size=1, seasonal=False,
suppress_warnings=True)
# This is a way to force it:
ARIMA(order=(0, 1, 0), out_of_sample_size=1).fit(vec)
# Want to make sure it works with exog arrays as well
exog = np.random.RandomState(1).rand(vec.shape[0], 2)
auto_arima(vec, exogenous=exog, out_of_sample_size=1,
seasonal=False,
suppress_warnings=True)
# This is a way to force it:
ARIMA(order=(0, 1, 0), out_of_sample_size=1).fit(vec, exogenous=exog)
Tying statsmodels' ARMA
, ARIMA
and SARIMAX
together under the hood of pyramid's ARIMA
is tricky and that's why we have had several bumps like this. Thanks for being patient, and as always keep reporting issues as you find them π
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