title: Interpretation of VARselect() results
body: <p>I read this post (<a href="https://stackoverflow.com/questions/14131676/selecting-an-appropriate-lag-for-a-regression-equation-and-how-to-interpret-the">Selecting an appropriate lag for a regression equation and how to interpret the results of VARselect</a>), covering the similar basics of my question already, but still am not sure about how to exactly interpret the results.</p>
  
  <p>My dataset (VARTotal_df) contains 14 economic and financial variables with 121 obs. each) My VARselect() results are in particular:</p>
  
  <pre><code>VARselect(VARTotal_df,lag.max=10,type="none") # AIC, HQ, SC and FPEsuggest lag of 8
  $selection
  AIC(n)  HQ(n)  SC(n) FPE(n) 
       8      8      8      7 
  
  $criteria
                    1            2            3            4            5            6            7    8    9   10
  AIC(n) 6.380974e+01 6.430259e+01 6.484109e+01 6.410062e+01 6.204580e+01 5.739413e+01          NaN -Inf -Inf -Inf
  HQ(n)  6.575063e+01 6.818436e+01 7.066375e+01 7.186418e+01 7.175024e+01 6.903945e+01          NaN -Inf -Inf -Inf
  SC(n)  6.859414e+01 7.387138e+01 7.919428e+01 8.323821e+01 8.596778e+01 8.610050e+01          NaN -Inf -Inf -Inf
  FPE(n) 5.253281e+27 9.861064e+27 2.516204e+28 2.861553e+28 2.023257e+28 5.558990e+27 -51057843500    0    0    0
  
  Warning messages:
  1: In log(sigma.det) : NaNs produced
  2: In log(sigma.det) : NaNs produced
  3: In log(sigma.det) : NaNs produced
  </code></pre>
  
  <p>Apparently, a lag of 8 is most appropriate. However, I am wondering whether this can be used as lag 7 contain NaN's and the lags 8 to 10 -Inf's. </p>
  
  <p>Clarification from a more knowledgeable person would be very appreciated!</p>