title: Time series Python ARIMA (testing,training and forecasting past dates available in data)
body: <p>I understand that separating data into training and testing provides a way to evaluate how well a model will perform with unseen data.</p>
  
  <p>I am training an ARIMA model and I have daily data from Oct.1 to Nov.22. I am interested in predicting some metric on Dec.14. Do I</p>
  
  <ol>
  <li>Train on all available data and use predict('2015-11-23','2015-12-14') or </li>
  <li>Split data into train and test to get performance metrics and use the model trained on training set (oct.1. to Nov.7) and do a predict that includes the test data as well dates into the future, e.g. predict('2015-11-8','2015-12-14').</li>
  </ol>
  
  <p>I hope my question makes sense, happy to clarify if you find this confusing. </p>
  
  <p>Thanks!</p>