I have a very simple Sarimax model using statsmodels:
mdl = sm.tsa.statespace.SARIMAX(ts_monthly, exog=ts_exog, order=(3,1,0)).fit()
where ts_monthly and ts_exog are pandas series indexed by date:
df
date vl_1 vl_2
2016-01-01 10 12
2016-02-01 14 1
2016-03-01 98 33
ts_monthly = df.vl_1
ts_exog = df.vl_2
The model fit works, but when I try to run a get_prediction, I get the following error:
ts = pd.Series([12,3,2], index=pd.date_range('2016-04-01', '2016-07-01', freq='M'))
mdl.get_prediction('2016-03-01', '2016-07-01', exog=ts, dynamic=False)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-135-c89e9e005a31> in <module>()
6 print(mdl.summary())
7 _ = mdl.plot_diagnostics()
----> 8 pred = mdl.get_prediction(start=start_date, end=end_date, exog=ts_exog, dynamic=False)
9 pred_ci = pred.conf_int()
10
C:\Users\myuer\bin\anaconda3\lib\site-packages\statsmodels\tsa\statespace\sarimax.py in get_prediction(self, start, end, dynamic, exog, **kwargs)
1901 ' appropriate shape. Required %s, got %s.'
1902 % (str(required_exog_shape),
-> 1903 str(exog.shape)))
1904 exog = np.c_[self.model.data.orig_exog.T, exog.T].T
1905
ValueError: Provided exogenous values are not of the appropriate shape. Required (3, 1), got (3,).
Any ideas of what kind of shape the prediction exogenous series must be?