[R] AR(2) coefficient interpretation

[Stephen Oman]

As I need your urgent help so let me modify my question. I imported the
following data set to R and run the statements i mentioned in my previous
reply 
   Year Month   Period     a    b      c
1  2008   Jan 2008-Jan 105,536,785  9,322,074  9,212,111
2  2008   Feb 2008-Feb 137,239,037 10,986,047 11,718,202
3  2008   Mar 2008-Mar 130,237,985 10,653,977 11,296,096
4  2008   Apr 2008-Apr 133,634,288 10,582,305 11,729,520
5  2008   May 2008-May 161,312,530 13,486,695 13,966,435
6  2008   Jun 2008-Jun 153,091,141 12,635,693 13,360,372
7  2008   Jul 2008-Jul 176,063,906 13,882,619 15,202,934
8  2008   Aug 2008-Aug 193,584,660 14,756,116 16,083,263
9  2008   Sep 2008-Sep 180,894,120 13,874,154 14,524,268
10 2008   Oct 2008-Oct 196,691,055 14,998,119 15,802,627
11 2008   Nov 2008-Nov 184,977,893 13,748,124 14,328,875

and the AR result is
Call:
arima(x = a, order = c(2, 0, 0))

Coefficients:
         ar1     ar2  intercept
      0.4683  0.4020     5.8654
s.e.  0.2889  0.3132     2.8366

sigma^2 estimated as 4.115:  log likelihood = -24.04,  aic = 56.08

The minimum mount of a is more than 100 million and the intercept is 5.86
based on the result above. 
If I placed all values into the formula then Xt=5.8654+0.4683*(184,977,893
)+0.4020*(196,691,055 )= 165,694,957.27. Do you think that makes sense? Did
i interpret the result incorrectly?

Also, i submit the following statement for the prediction of next period

> predict<-predict(fit, n.ahead=1)
> predict

it came out the value of 9.397515 below and I have no idea about how to
interpret this value. Please help. 

$pred
Time Series:
Start = 12 
End = 12 
Frequency = 1 
[1] 9.397515

$se
Time Series:
Start = 12 
End = 12 
Frequency = 1 
[1] 2.028483



Stephen Oman wrote:
> 
> I am a beginner in using R and I need help in the interpretation of AR
> result by R.  I used 12 observations for my AR(2) model and it turned out
> the intercept showed 5.23 while first and second AR coefficients showed
> 0.40 and 0.46. It is because my raw data are in million so it seems the
> intercept is too small and it doesn't make sense. Did i make any mistake
> in my code? My code is as follows:
> 
> r<-read.table("data.txt", dec=",", header=T)
> attach(r)
> fit<-arima(a, c(2,0,0))
> 
> Thank you for your help first.
> 
> 

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