From: Amir Safari <amsa36060_at_yahoo.com>

Date: Tue 16 Aug 2005 - 04:05:02 EST

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 Received on Tue Aug 16 04:18:17 2005

Date: Tue 16 Aug 2005 - 04:05:02 EST

Dear David, Dear Gabor , Dear All,

Many thanks for your reply and informative emails.
Actually I think it is difficult to define for example a regression model within a SVM framework theoretically and experimentaly. What we have to do is that we work on input data to construct model befor entering data into SVM. This procedure ( building a certain model) can be viewed as a preprocessing of data and or model building. Doesn't it?
Parametric models are basically rejected, because SVM learns only nonparametric ones.
I would be very appreciated again if I have any correction or guidance.
Have a fun,

Amir

<ggrothendieck@gmail.com> wrote:

On 8/12/05, Gabor Grothendieck wrote:

> David, Please correct me if I am wrong but I think svm partially works

*> with dyn although I don't remember what the specific limitations were.
**> Its possible that what works already is enough for Amir. For example,
**>
**> library(e1071)
**> library(dyn)
**> set.seed(1)
**> y <- ts(rnorm(100))
**> y.svm <- dyn$svm(y ~ lag(y))
*

The above statement should have been y.svm <- dyn$svm(y ~ lag(y,-1)) since we want to bring the previous value of y forward so that it is being used to predict y (rather than predicting y by bringing the future value of y backward). In R positive values for the lag move the series backward and negative values move it forward.

> yp <- predict(y.svm)

*> ts.plot(y, yp, col = 1:2)
**>
**> On 8/12/05, David Meyer wrote:
**> > Amir,
**> >
**> > >
**> > > Suppose that we want to regress for example a certain autoregressive
**> > > model using SVM. We have our data and also some fixed kernels in
**> > > libSVM behinde e1071 in front. The question: Where can we insert our
**> > > certain autoregressive model ? During creating data frame ?
**> >
**> > Yes, I think.
**> >
**> > > Or perhaps we can make a
**> > > relationship between our variables ended to desired autoregressive
**> > > model ?
**> >
**> > Gabor Grothendieck's `dyn` package provides support for the use of
**> > general regression functions for time series analysis, and we are
**> > currently struggling to integrate the e1071 interface into that
**> > framework (but nothing is ready so far). Is it that kind of support you
**> > have been looking for?
**> >
**> > Cheers,
**> > David
**> >
**> > >
**> > > Thanks a lot for your help.
**> > > Amir Safari
**> > >
**> > >
**> > >
**> > >
**> > > __________________________________________________
**> > > Do You Yahoo!?
*

> > > http://mail.yahoo.com

*> >
**> >
**> > --
**> > Dr. David Meyer
**> > Department of Information Systems and Operations
**> >
**> > Vienna University of Economics and Business Administration
**> > Augasse 2-6, A-1090 Wien, Austria, Europe
**> > Fax: +43-1-313 36x746
**> > Tel: +43-1-313 36x4393
**> > HP: http://wi.wu-wien.ac.at/~meyer/
**> >
**> > ______________________________________________
**> > 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
**> >
*

>

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue Aug 16 04:18:17 2005

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