help on vector auto-regressive model

Right it's good to mention if the question was asked on antoher list,
to avoid cross-posting.

I'm not convinced by the answer there, neither by the question itself:
I'm indeed not sure goodness of fit is a relevant notion for time
series data.

To the answer: ACF/PACF and normality tests just tell you if you the
assumption needed for inference seem to hold or not. In analogy to the
usual linear regression case, this is not the point whe nassesing
goodness of fit I believe.

To the question: for time series model where you add lags, indicators
such R^2 go to 1 due to the presence of the lagged variables, so are
not indicative... You may still look at individual R^2 and make
comparisons which variable is well explained in the model and which is
not (for that rather use FEVD maybe)... But overall R^2 does not exist
to my knowledge (nor makes sense in my opinion).

Well this is rather a personal view...

Hope this helps

Mat

2009/8/24 Megh Dal <megh700004 at yahoo.com>:

help on vector auto-regressive model

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