[R] How to insert a certain model in SVM regarding to fixed kernels

[Gabor Grothendieck]

On 8/12/05, Gabor Grothendieck <ggrothendieck at gmail.com> 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 <david.meyer at wu-wien.ac.at> 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
> > >
> > >
> > >
> > >
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