content: """
  Using dates with timeseries models
  """
  import statsmodels.api as sm
  import pandas as pd
  
  # Getting started
  # ---------------
  
  data = sm.datasets.sunspots.load()
  
  # Right now an annual date series must be datetimes at the end of the year.
  
  dates = sm.tsa.datetools.dates_from_range('1700', length=len(data.endog))
  
  # Using Pandas
  # ------------
  
  # Make a pandas TimeSeries or DataFrame
  endog = pd.TimeSeries(data.endog, index=dates)
  
  # and instantiate the model
  ar_model = sm.tsa.AR(endog, freq='A')
  pandas_ar_res = ar_model.fit(maxlag=9, method='mle', disp=-1)
  
  # Let's do some out-of-sample prediction
  pred = pandas_ar_res.predict(start='2005', end='2015')
  print(pred)
  
  # Using explicit dates
  # --------------------
  
  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)
  
  # This just returns a regular array, but since the model has date information
  # attached, you can get the prediction dates in a roundabout way.
  
  print(ar_res.data.predict_dates)
  
  # This attribute only exists if predict has been called. It holds the dates
  # associated with the last call to predict.
  #..TODO: should this be attached to the results instance?
  