title: How do i correctly predict the humidity values?
body: <p>I have the following input:</p>
  
  <pre><code>startDate = "2013-01-01"
  endDate = "2013-01-01"
  knownTimestamps = ['2013-01-01 00:00','2013-01-01 01:00','2013-01-01     02:00','2013-01-01 03:00','2013-01-01 04:00',
             '2013-01-01 05:00','2013-01-01 06:00','2013-01-01 08:00','2013-01-01 10:00','2013-01-01 11:00',
             '2013-01-01 12:00','2013-01-01 13:00','2013-01-01 16:00','2013-01-01 17:00','2013-01-01 18:00',
             '2013-01-01 19:00','2013-01-01 20:00','2013-01-01 21:00','2013-01-01 23:00']
  humidity = ['0.62','0.64','0.62','0.63','0.63','0.64','0.63','0.64','0.48','0.46','0.45','0.44','0.46','0.47','0.48','0.49','0.51','0.52','0.52']
  timestamps = ['2013-01-01 07:00','2013-01-01 09:00','2013-01-01 14:00','2013-01-01 15:00','2013-01-01 22:00']
  </code></pre>
  
  <p>And I am using following function to predict the humidity values using AR model in python.</p>
  
  <pre><code>from statsmodels.tsa.arima_model import ARIMA
  def predictMissingHumidity(startDate, endDate, knownTimestamps, humidity, timestamps):
  data_prediction = pd.DataFrame({'knownTimestamps': knownTimestamps,'humidity': humidity})
  print(data_prediction.head(10))
  history = [float(x) for x in data_prediction.humidity]
  predictions = []
  test = timestamps
  for t in range(len(test)):
      model = ARIMA(history, order=(2,2,0))
      model_fit = model.fit(disp=0)
      output = model_fit.forecast()
      yhat = output[0]
      predictions.append(float(yhat))
      obs = test[t]
      history.append(float(obs))
  print(predictions)
  return predictions
  </code></pre>
  
  <p>The model predict the same value of humidity for the values in time stamp list.</p>
  
  <pre><code>res = predictMissingHumidity(startDate, endDate, knownTimestamps, humidity, timestamps) 
  print(res)
  
  
  output = [0.5287247355700563, 0.5287247355700563, 0.5287247355700563,
   0.5287247355700563, 0.5287247355700563] 
  </code></pre>
  
  <p>Can someone tell me where I am wrong?</p>