Dates in timeseries models

In [1]:
from __future__ import print_function
import statsmodels.api as sm
import numpy as np
import pandas as pd
/build/statsmodels-0.8.0/.pybuild/cpython3_3.7_statsmodels/build/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.
  from pandas.core import datetools
/usr/lib/python3/dist-packages/scipy/_lib/_util.py:18: RuntimeWarning: invalid value encountered in multiply
  out = np.ones(shape, dtype=bool) * value

Getting started

In [2]:
data = sm.datasets.sunspots.load()

Right now an annual date series must be datetimes at the end of the year.

In [3]:
from datetime import datetime
dates = sm.tsa.datetools.dates_from_range('1700', length=len(data.endog))

Using Pandas

Make a pandas TimeSeries or DataFrame

In [4]:
endog = pd.Series(data.endog, index=dates)

Instantiate the model

In [5]:
ar_model = sm.tsa.AR(endog, freq='A')
pandas_ar_res = ar_model.fit(maxlag=9, method='mle', disp=-1)

Out-of-sample prediction

In [6]:
pred = pandas_ar_res.predict(start='2005', end='2015')
print(pred)
2005-12-31    20.003291
2006-12-31    24.703985
2007-12-31    20.026128
2008-12-31    23.473653
2009-12-31    30.858578
2010-12-31    61.335465
2011-12-31    87.024710
2012-12-31    91.321279
2013-12-31    79.921656
2014-12-31    60.799552
2015-12-31    40.374907
Freq: A-DEC, dtype: float64

Using explicit dates

In [7]:
ar_model = sm.tsa.AR(data.endog, dates=dates, freq='A')
ar_res = ar_model.fit(maxlag=9, method='mle', disp=-1)
pred = ar_res.predict(start='2005', end='2015')
print(pred)
[20.00329132 24.70398499 20.02612756 23.47365323 30.85857776 61.33546479
 87.02471007 91.3212787  79.92165617 60.79955229 40.37490725]

This just returns a regular array, but since the model has date information attached, you can get the prediction dates in a roundabout way.

In [8]:
print(ar_res.data.predict_dates)
DatetimeIndex(['2005-12-31', '2006-12-31', '2007-12-31', '2008-12-31',
               '2009-12-31', '2010-12-31', '2011-12-31', '2012-12-31',
               '2013-12-31', '2014-12-31', '2015-12-31'],
              dtype='datetime64[ns]', freq='A-DEC')

Note: This attribute only exists if predict has been called. It holds the dates associated with the last call to predict.