Dear Spencer,



Thank you very much for your attention on my problem. According to your
advice I did some home work on this problem, but unfortunately I could not
solve my problem.





Suppose I have a dataset of length 300 with 2 variables. And I want to fit a
VAR model on this of order 2.



I went through the function mAr.est and got understand that, here 'K' is a
matrix with (300-2) rows and 7 columns. the first col. consists only 1, next
two columns consist of lagged values of two variables with lag-length 2,
next two col. consist of lagged value with lag length-1, and next two cols
are for lag-length-0.



Next, they add additional a 7-7 matrix to K. For this matrix diagonal
elements are the square root of sum of square of elements of K (col. wise)
and rest of the elements are 0.



I feel that this matrix, that is added to K, is the key matrix for any type
of modification that you prescribed. Therefore for experimental purpose I
put NA against one of its off-diagonal elements. But I got error.



However I cannot understand why they put such figures for diagonal and
off-diagonal elements of that matrix.



Can you suggest me any solution more specifically?





Thanks and regards,

Arun


On 9/4/06, Spencer Graves <spencer.graves@pdf.com> wrote:
>
>       Have you tried 'RSiteSearch("multivariate autoregression",
> "functions")'?  This produced 14 hits for me just now, the first of
> which mentions a package 'MSBVAR'.  Have you looked at that?
>
>       If that failed, I don't think it would be too hard to modify
> 'mAr.est' to do what you want.  If it were my problem, I might a local
> copy of the function, then add an argument accepting a 2 or
> 3-dimensional array with numbers for AR coefficients to be fixed and NAs
> for the coefficients.  Then I'd use 'debug' to walk through the function
> line by line until I figured out how to modify the function to do what I
> wanted.  I haven't checked all the details, so I don't know for sure if
> this would work, but the function contains a line 'R = qr.R(qr((rbind(K,
> diag(scale)))), complete = TRUE)' which I would start by decomposing,
> possibly starting as follows:
>
>       Z <-     rbind(K, diag(scale)
>
> I'd figure out how the different columns of Z relate to my problem, then
> modify it appropriately to get what I wanted.
>
>       Another alternative would be to program it from scratch using
> something like 'optim' to minimize the sum of squares of residuals over
> the free parameters in my AR matrices.   I'm confident I could make this
> work, even if the I somehow could not get it with either of the other two.
>
>       There may be something else  better, e.g., a Kalman filter
> representation, but I can't think how to do that off the top if my head.
>
>       Hope this helps.
>       Spencer Graves
>
> Arun Kumar Saha wrote:
> > Dear R users,
> >
> > I am using mAr package to fit a Vector autoregressive model to my data.
> But
> > here I want to put some predetermined values for some elements in
> > coefficient matrix that mAr.est going to estimate. For example if p=3
> then I
> > want to put A3[1,3] = 0 and keep rest of the elements of coefficient
> > matrices to be determined by mAr.est.
> >
> > Can anyone please tell me how can I do that?
> >
> > Sincerely yours,
> > Arun
> >
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>



-- 
Arun Kumar Saha, M.Sc.[C.U.]
S T A T I S T I C I A N    [Analyst]
RISK  MANAGEMENT  DIVISION
Transgraph Consulting [www.transgraph.com]
Hyderabad, INDIA
Contact #  Home: (91-033) 25558038
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            arun.kumar.saha@gmail.com

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