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 <[EMAIL PROTECTED]> 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 <[EMAIL PROTECTED]> 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]] > > > > > > > > ------------------------------------------------------------------------------ > Notice: This e-mail message, together with any attachment...{{dropped}}
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