title: How to get predictions using X-13-ARIMA in python statsmodels
body: <p>I'm trying to run X-13-ARIMA model from statsmodels library in python 3.</p>
  
  <p>I found this example in statsmodels documentation:</p>
  
  <pre><code>dta = sm.datasets.co2.load_pandas().data
  dta.co2.interpolate(inplace=True)
  dta = dta.resample('M').sum()
  
  res = sm.tsa.x13_arima_select_order(dta.co2)
  print(res.order, res.sorder)
  
  results = sm.tsa.x13_arima_analysis(dta.co2)
  
  fig = results.plot()
  fig.set_size_inches(12, 5)
  fig.tight_layout()
  </code></pre>
  
  <p>This works fine, but I also need to predict future values of this time series. The <code>tsa.x13_arima_analysis()</code> function contains <code>forecast_years</code> parameter, so I suppose it should be possible. However; the <code>results</code> object doesn't seem to change no matter what value of <code>forecast_years</code> parameter I choose.</p>
  
  <p>How can I get the forecast values?</p>