I think you mis-understood. And perhaps you read in a haste, or you were
just in a bad mood today.

I think on this mailing-list, many people come for help on a R related
issue, they know something theoretically, but since they are new to R, they
want to use R, they want to use R to help do applied things.

For me, there is a missing link between my understanding of splines from the
books(which are abstract) and a usage example in R. That's something I am
looking for. I believe it is very appropriate.

If you don't know, or don't want to say anything helpful, please just don't
say anything. It is not about a gun pointing, it is about a learning process
which is very specific to R.

Please kindly try not to say negative things, and try to discourage people
from learning new things.

On 2/27/06, Liaw, Andy <andy_liaw@merck.com> wrote:
>
> If you do not understand what ns() outputs, nor descriptions of splines in
> books, perhaps it's not an appropriate tool for you.  Look for something
> that you understand (or can understand after some reading).  No one is
> pointing a gun to your head and tell you to use splines, I hope.
>
> If you have a hard time understanding what you read in books, it's
> unrealistic to expect a mailing list about a software to teach you.
>
> Andy
>
> From: Michael
> >
> > Have you seen an example on how to do it in R? I found no practical
> > examples...
> >
> > On 2/27/06, vito muggeo <vmuggeo@dssm.unipa.it> wrote:
> > >
> > > Dear Micheal,
> > >
> > > > the output of the "ns" function in R is "basis matrix", but then
> > > Yes you are right, the output of the ns(x, df) is the basis
> > matrix of a
> > > natural cubic spline with df degrees of freedom. See ?ns (in package
> > > splines) on how to specify df or knots or ..
> > >
> > > Fitting y~ns(x,df) yields a smooth curve given by a linear
> > combination
> > > of the basis functions (the single colums of the basis
> > matrix) by the
> > > estimated coefficients (returned by the fitted model).
> > >
> > > As far as I know, a tensor product is usually employed to
> > > multidimensional smoothing and the multidimensional basis
> > is formed via
> > > the kronecker product of the marginal bases.
> > >
> > > Finally, last but not least: Probably you need some statistical
> > > backaground on spline fitting..
> > > Please, read some statistical papers/books on such topic
> > (for instance
> > > see references in packages splines, mgcv)
> > >
> > > best,
> > > vito
> > >
> > > Michael wrote:
> > > > Hi all,
> > > >
> > > > Could anybody recommend some easy-to-understand and example based
> > > > notes/tutorials on how to use cubic splines to do filtering on
> > > > multi-dimension data?
> > > >
> > > > I am confused by the 1-dimensional case, and more confused by
> > > > multi-dimensional case.
> > > >
> > > > I found all the books suddenly become very abstract when
> > it comes to
> > > this
> > > > subject.
> > > >
> > > > They don't provide examples in R or Splus at all.
> > > >
> > > > Specifically, I don't know how to provide data "x" to the
> > "ns" function
> > > in
> > > > R,
> > > >
> > > > and I don't understand what should be the output matrix,
> > and how to use
> > > the
> > > > output matrix to "filter" data?
> > > >
> > > > Books mention about basis matrix, design matrix, model
> > matrix, data
> > > matrix,
> > > > etc. I got lost.
> > > >
> > > > I presume the output of the "ns" function in R is "basis
> > matrix", but
> > > then
> > > > how do I use it?  How to form tensor-product?
> > > >
> > > > I don't understand it at all.
> > > >
> > > > Please help me!
> > > >
> > > > Thank you very much!
> > > >
> > > >       [[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
> > > >
> > >
> > > --
> > > ====================================
> > > Vito M.R. Muggeo
> > > Dip.to Sc Statist e Matem `Vianelli'
> > > Università di Palermo
> > > viale delle Scienze, edificio 13
> > > 90128 Palermo - ITALY
> > > tel: 091 6626240
> > > fax: 091 485726/485612
> > > ====================================
> > >
> >
> >       [[alternative HTML version deleted]]
> >
> >
>
>
>
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