Is this option (number of nearest neighbors) translate-able into bandwidth?
In reading the kknn article, it seems like it might be but I'm still not
exactly sure how. Unfortunately this is an important issue as the end users
are used to using certain bandwidth values for their work.

It may be more efficient to ask, more generally, how would I reproduce this
command:

ksmooth(x, y, "normal", bandwidth=10)

where x and y are ratio level variables, using kknn?

Thanks for your patience and continued assistance.


On Sat, Sep 12, 2009 at 5:19 PM, Gabor Grothendieck <ggrothendieck@gmail.com
> wrote:

> You can specify the number of nearest neighbors.
>
> On Sat, Sep 12, 2009 at 5:16 PM, Bryan <thespamhouse@gmail.com> wrote:
> > 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
> > <ggrothendieck@gmail.com> wrote:
> >>
> >> What about kknn -- that was listed as having the triangular
> distribution?
> >>
> >>
> >> On Sat, Sep 12, 2009 at 3:42 PM, Bryan <thespamhouse@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
> >> > <ggrothendieck@gmail.com> wrote:
> >> >>
> >> >> Try:
> >> >>
> >> >> RSiteSearch("kernel triangular")
> >> >>
> >> >> On Sat, Sep 12, 2009 at 1:51 PM, Bryan <thespamhouse@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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