I originally looked over kknn because I need to be able to specify a
bandwidth parameter. I am trying to replicate some previous non-R work in
R, so I can't stray to far from the procedure used there. In reading the
paper referenced in the docs, I see that kknn can reduce to the
Nadaraya–Watson estimator, which is where I need to be, but I'm not sure how
to manipulate the bandwidth, as would be possible in other methods. Can you
clarify this at all?
Bryan
On Sat, Sep 12, 2009 at 3:46 PM, Gabor Grothendieck <ggrothendi...@gmail.com
> wrote:
> What about kknn -- that was listed as having the triangular distribution?
>
>
> On Sat, Sep 12, 2009 at 3:42 PM, Bryan <thespamho...@gmail.com> wrote:
> > Gabor,
> >
> > Thanks for your quick reply (on a weekend even!) I've looked through the
> > results of the search you recommended, and several related searches, and
> > don't see anything exceptionally helpful. Kernel regression is a
> relatively
> > new analysis for me; I apologize for needing a little more direction.
> >
> > I've understand that it is connected to local polynomial regression but I
> > can't seem to have any success from that direction either. At this point
> the
> > only package that is giving smoothed estimates as I would expect is
> ksmooth
> > - which doesn't include the appropriate distribution.
> >
> > Best,
> > Bryan
> >
> >
> > On Sat, Sep 12, 2009 at 1:55 PM, Gabor Grothendieck
> > <ggrothendi...@gmail.com> wrote:
> >>
> >> Try:
> >>
> >> RSiteSearch("kernel triangular")
> >>
> >> On Sat, Sep 12, 2009 at 1:51 PM, Bryan <thespamho...@gmail.com> wrote:
> >> > Hello,
> >> >
> >> > I am trying to get fitted/estimated values using kernel regression and
> a
> >> > triangular kernel. I have found packages that easily fit values from
> a
> >> > kernel regression (e.g. ksmooth) but do not have a triangular
> >> > distribution
> >> > option, and density estimators that have triangular distribution
> options
> >> > that I can't seem to use to produce estimated values (e.g. density).
> >> > Any
> >> > help is appreciated.
> >> >
> >> > Bryan
> >> >
> >> > [[alternative HTML version deleted]]
> >> >
> >> > ______________________________________________
> >> > R-help@r-project.org 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.
> >> >
> >
> >
>
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