Suppose I have two var x and y,now I want to fits a natural cubic
spline in x to y,at the same time create new var containing the smoothed values of y. How can I get it? ______________________________________________ [hidden email] 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. |
If one enters:
??"spline" ... You get quite a few matches. The one in the stats functions that probably answers your specific questions is: "splinefun {stats} R Documentation Interpolating Splines Description Perform cubic (or Hermite) spline interpolation of given data points, returning either a list of points obtained by the interpolation or a function performing the interpolation." "splinefun returns a function with formal arguments x and deriv, the latter defaulting to zero. This function can be used to evaluate the interpolating cubic spline (deriv=0), or its derivatives (deriv=1,2,3) at the points x, where the spline function interpolates the data points originally specified. This is often more useful than spline." Perhaps you need to review from you basic intro material regarding help.search("text") # or ??"text" # possibilities. -- David Winsemius On Mar 30, 2009, at 10:58 PM, minben wrote: > Suppose I have two var x and y,now I want to fits a natural cubic > spline in x to y,at the same time create new var containing the > smoothed values of y. How can I get it? > > ______________________________________________ > [hidden email] 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. David Winsemius, MD Heritage Laboratories West Hartford, CT ______________________________________________ [hidden email] 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. |
Hi,
if you are looking for *natural* cubic splines (linear beyond the outer knots), you could use rcs() in Frank Harrell's Design package. HTH, Stephan David Winsemius schrieb: > If one enters: > > ??"spline" > > ... You get quite a few matches. The one in the stats functions that > probably answers your specific questions is: > > "splinefun {stats} R Documentation > Interpolating Splines Description > Perform cubic (or Hermite) spline interpolation of given data points, > returning either a list of points obtained by the interpolation or a > function performing the interpolation." > > "splinefun returns a function with formal arguments x and deriv, the > latter defaulting to zero. This function can be used to evaluate the > interpolating cubic spline (deriv=0), or its derivatives (deriv=1,2,3) > at the points x, where the spline function interpolates the data points > originally specified. This is often more useful than spline." > > Perhaps you need to review from you basic intro material regarding > help.search("text") # or > ??"text" # possibilities. > ______________________________________________ [hidden email] 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. |
In reply to this post by minben
Hello:
If B-splines will suffice, there are many capabilities in R for that. My favorite is the 'fda' package, but 'splines' and other packages are also good. The "splinefun" function in the "base" package returns a function to compute spline interpolations optionally using a natural spline. However, that is an interpolation spline and therefore does no smoothing. To find other options for natural splines, I suggest you try the CRAN packages splines, mboost, pspline, Design, and mgcv. I found them using the "RSiteSearch" packages available from R-Forge via 'install.packages("RSiteSearch", repos="http://r-forge.r-project.org")', which also identified the "siggenes" package (which is not on CRAN). I don't know if any of these actually use natural splines, but this gives you a reasonably short list to consider. Hope this helps. Spencer Graves p.s. The following are the commands I used with the "RSiteSearch" package: library(RSiteSearch) natSpl <- RSiteSearch.function('natural spline') str(natSpl) summary(natSpl) natSpl[1:23, c(1, 4, 5, 7)] minben wrote: > Suppose I have two var x and y,now I want to fits a natural cubic > spline in x to y,at the same time create new var containing the > smoothed values of y. How can I get it? > > ______________________________________________ > [hidden email] 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. > > ______________________________________________ [hidden email] 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. |
In reply to this post by Stephan Kolassa
The splinefun documentation indicates that "natural" is one of the
types of cubic spline options available. Does rcs actually do fitting? Such would not be my expectation on reading the documentation and I do not see any examples of such functionality in the help pages. -- David Winsemius On Mar 31, 2009, at 6:09 AM, Stephan Kolassa wrote: > Hi, > > if you are looking for *natural* cubic splines (linear beyond the > outer knots), you could use rcs() in Frank Harrell's Design package. > > HTH, > Stephan > > > David Winsemius schrieb: >> If one enters: >> ??"spline" >> ... You get quite a few matches. The one in the stats functions >> that probably answers your specific questions is: >> "splinefun {stats} R Documentation >> Interpolating Splines Description >> Perform cubic (or Hermite) spline interpolation of given data >> points, returning either a list of points obtained by the >> interpolation or a function performing the interpolation." >> "splinefun returns a function with formal arguments x and deriv, >> the latter defaulting to zero. This function can be used to >> evaluate the interpolating cubic spline (deriv=0), or its >> derivatives (deriv=1,2,3) at the points x, where the spline >> function interpolates the data points originally specified. This is >> often more useful than spline." >> Perhaps you need to review from you basic intro material regarding >> help.search("text") # or >> ??"text" # possibilities. > > David Winsemius, MD Heritage Laboratories West Hartford, CT ______________________________________________ [hidden email] 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. |
Hi David,
David Winsemius schrieb: > The splinefun documentation indicates that "natural" is one of the types > of cubic spline options available. That sounds good, didn't know that... rcs() has the advantage of coming with a book (Harrell's "Regression Modeling Strategies"). > Does rcs actually do fitting? Such would not be my expectation on > reading the documentation and I do not see any examples of such > functionality in the help pages. Nope, but you can include rcs() within fitting functions, lm(foo~rcs(bar,3)), which makes more sense to me than having a spline function fit... Looks like better encapsulation to me. Best, Stephan ______________________________________________ [hidden email] 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. |
In reply to this post by David Winsemius
David Winsemius wrote:
> The splinefun documentation indicates that "natural" is one of the types > of cubic spline options available. > > Does rcs actually do fitting? Such would not be my expectation on > reading the documentation and I do not see any examples of such > functionality in the help pages. It expands a predictor into the truncated power basis functions for the natural cubic spline. This is an easier basis to use than the B-spline basis. rcs calls the Hmisc function rcspline.eval which you may want to look at first. Frank -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University ______________________________________________ [hidden email] 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.
Frank Harrell
Department of Biostatistics, Vanderbilt University |
In reply to this post by Stephan Kolassa
>>>>> "SK" == Stephan Kolassa <[hidden email]>
>>>>> on Tue, 31 Mar 2009 22:20:50 +0200 writes: SK> Hi David, SK> David Winsemius schrieb: >> The splinefun documentation indicates that "natural" is one of the types >> of cubic spline options available. SK> That sounds good, didn't know that... rcs() has the advantage of coming SK> with a book (Harrell's "Regression Modeling Strategies"). well, and splinefun() comes with R !!! >> Does rcs actually do fitting? Such would not be my expectation on >> reading the documentation and I do not see any examples of such >> functionality in the help pages. SK> Nope, but you can include rcs() within fitting functions, SK> lm(foo~rcs(bar,3)), which makes more sense to me than having a spline SK> function fit... Looks like better encapsulation to me. well, but ns() has been part of the S language for ages, and part of R since its very early days, exactly for the purpose to be used in something like lm(y ~ ns(.) + ..) So while rcs() may have extra merits, (I assume it does, as I assume Frank Harrell will have known about ns()), in order to solve the OP's problem, I still believe that "standard R" [and "good old S version 3 for that matter] contains all functionality needed. Martin Maechler, ETH Zurich SK> Best, SK> Stephan SK> ______________________________________________ SK> [hidden email] mailing list SK> https://stat.ethz.ch/mailman/listinfo/r-help SK> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html SK> and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [hidden email] 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. |
In reply to this post by Spencer Graves-3
>>>>> "SpG" == spencerg <[hidden email]>
>>>>> on Tue, 31 Mar 2009 07:35:07 -0700 writes: SpG> Hello: SpG> If B-splines will suffice, there are many capabilities in R for SpG> that. My favorite is the 'fda' package, but 'splines' and other SpG> packages are also good. SpG> The "splinefun" function in the "base" package returns a function SpG> to compute spline interpolations optionally using a natural spline. SpG> However, that is an interpolation spline and therefore does no smoothing. SpG> To find other options for natural splines, I suggest you try the SpG> CRAN packages splines, mboost, pspline, Design, and mgcv. I found them SpG> using the "RSiteSearch" packages available from R-Forge via SpG> 'install.packages("RSiteSearch", repos="http://r-forge.r-project.org")', SpG> which also identified the "siggenes" package (which is not on CRAN). I SpG> don't know if any of these actually use natural splines, but this gives SpG> you a reasonably short list to consider. Just a quick note with a small correction: 'splines' is *not* a CRAN, but a "standard R" aka "base R" package that has "always" been "with us", and in my eyes contains (almost IIRC) everything you'd ever want for univariate natural splines. In particular, note the 'Priority' and 'Author' fields in > packageDescription("splines") Martin Maechler, ETH Zurich SpG> Hope this helps. SpG> Spencer Graves SpG> p.s. [.........] SpG> minben wrote: >> Suppose I have two var x and y,now I want to fits a natural cubic >> spline in x to y,at the same time create new var containing the >> smoothed values of y. How can I get it? ______________________________________________ [hidden email] 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. |
Powered by Nabble | Edit this page |