title: Build ARIMA model
body: <p>My data is timeseries :</p>
  <pre><code>library(forecast)    
  library(Mcomp)
  ts.data&lt;- subset(M3, 12)[[551]]
  print(ts.data)
  </code></pre>
  <p>Output:</p>
  <pre><code>Series: M551
  Type of series: INDUSTRY
  Period of series: MONTHLY
  Series description: Lumber, softwoods, western pine, production
  
  HISTORICAL data
         Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec
  1983  5960  6320  7050  7080  7170  7620  7000  7790  7830  7580  6620  6860
  1984  7240  6550  8730  8690  7650  7950  7210  7880  7040  7940  7290  5750
  1985  6410  6230  7260  8220  7770  7830  7590  9210  8340  8660  7330  7000
  1986  7500  7430  8350  9010  8470  8900  8720  9710 10070  9610  8410  8640
  1987  8500  8920 10470  8960  9390 10630  9380 10050  9030 10580  9350  8810
  1988  9300 10430 10570 10440 10120  8780  7460  8230  9830 10260  9270  9260
  1989  9260  8150  9930  8840  9150 10230  9340 10170  9150 10420  8690  8960
  1990  9960  9050 10430  9650  9350  8790  8550  8790  7590  8730  7520  6110
  1991  7450  7230  7680  8270  8060  8210  8260  8910  8540  8180  7430  6880
  1992  7360  7560  8800  7550  7900  8320  7430                              
  
  FUTURE data
        Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec
  1992                                    7650 7460 8580 7300 6530
  1993 7070 6940 7060 7470 6190 6310 7090 7310 6310 7270 7240 6410
  1994 7470                                   
  </code></pre>
  <p><em>How can i build ARIMA model and then find the Mean Absolute Error (MAE) of the model ?</em></p>
  <p>Any thoughts to start would be helpfull.</p>