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[EMAIL PROTECTED] (Bush will disarm all workers next) wrote in message news:<[EMAIL 
PROTECTED]>...
> Ran summary.arma(arma(inp, order=c(2,2))) on a timeseries data set and
> generated these results:
> 
> 
> Call:
> arma(x = inp, order = c(2, 2))
> 
> Model:
> ARMA(2,2)
> 
> Residuals:
>      Min       1Q   Median       3Q      Max
> -0.40833 -0.37282 -0.33614 -0.06072 60.63911
> 
> Coefficient(s):
>             Estimate  Std. Error  t value Pr(>|t|)
> ar1        1.9484320          NA       NA       NA
> ar2       -0.9486320          NA       NA       NA
> ma1       -0.9577766          NA       NA       NA
> ma2       -0.0009986   0.0503448    -0.02    0.984
> intercept  0.0382860          NA       NA       NA
> 
> Fit:
> sigma^2 estimated as 10.01,  Conditional Sum-of-Squares = 3945.79, 
> AIC = 2051.33
> 
> How are the coefficients interpreted? Is there a way to
> predict/forecast?
> 
> Thanks 
> Dakshin


Dakshin,

There is no need to interpret thos model as it is non-invertible and
thus an invalid model


By inspection the two ar coefficients when added together are just
about 1.0 which indicates non-invertibilty.

  ar1        1.9484320          NA       NA       NA
> ar2       -0.9486320          NA       NA       NA


Older programs just simply fitting senseless AR/MA structures are to
be avoided like the plague. Programs that simply fit higher and higher
orders that don't test for invertibility are to be studiously avoided.

Perhaps you might want to get some freeware , which actually verbally
describes the equation ....http://www.autobox.com/freef.exe ..The
program is called FreeFore . It is so much fun to play with that many
users have suggested the name ForePlay ! (LOL !)


hope this helps ..

David P. Reilly
AUTOMATIC FORECASTING SYSTEMS

215-675-0652

P.S. For some details on FreeFore click on
http://www.autobox.com/ffpro.doc

for other info please see
http://www.autobox.com/pdfs/whytheyswitched.pdf

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