search for: splinefun

Is there a way of calculating the derivative of a function returned by splinefun()? Such a function is a cubic spline, whence it has a calculable derivative, but is there a (simple) way of getting at it? One workaround that I have thought of is to take a fine grid of points, evaluate the function returned by splinefun() at these points, put an interpolating spline through the...

...oding: 7bit Content-Disposition: inline G'day Greg, On Mon, 6 Oct 2008 19:50:13 +0200 (CEST) Greg.Snow at imail.org wrote: > This is a low priority bug that has been around for a while, but I > came across it again while alpha testing 2.8. Indeed, that bug must have been around since splinefun was changed to return a function with a deriv argument. Looks as if the person who produced the initial patch didn't really think through all possibilities. ;-) > The resulting function for splinefun gives incorrect deriv values > when x is less than the smallest x-value used to create...

...knot it should be taken as zero. So the attached patch solves the problem in what some might consider a more elegant manner. :) With the patch "make check FORCE=FORCE" works on my machine and it also solves your example: R> x <- 1:10 R> y <- sin(x) R> R> splfun <- splinefun(x,y, method='natural') R> R> # these should be linear (and are) R> splfun( seq(0,1, 0.1) ) [1] 0.5682923 0.5956102 0.6229280 0.6502459 0.6775638 0.7048816 [7] 0.7321995 0.7595174 0.7868352 0.8141531 0.8414710 R> R> # these should all be the same R> splfun( seq(0,1, 0...

This is a low priority bug that has been around for a while, but I came acr= oss it again while alpha testing 2.8. The resulting function for splinefun gives incorrect deriv values when x is= less than the smallest x-value used to create the function (at least in on= e circumstance), but does the correct thing for x greater than the largest = x-value. Here is an example: > x <- 1:10 > y <- sin(x) > > splfun <- splinefun(x,y...

Hi, In my version of R, the stats package splinefun code for fitting a Fritsch and Carlson monotonic spline does not appear to guarantee a monotonic result. If two adjoining sections both have over/undershoot the way the resulting adjustment of alpha and beta is performed can give modified values which still do not satisfy the required constraints....

hello, is it possible to do something like splinefun(x,y), but with a 3rd dim? for example, if i have a 2-dim system like: x<-1:100 y<-rexp(100,1) func<-splinefun(x,sort(y)) func(n) # returns interpolated value of y (after sorting) given x=n # i can check this by: plot(x,sort(y)) lines(spline(x,sort(y))) Can i do the same thing...

I am working with the function: splinefun() ... When plugging in the variables, I get the function program as if though having only entered '"splinefun". only way to get the values is by spline(xxx,yyy, n=length(xxx)/10, ties = mean)$x and spline(xxx,yyy, n=length(xxx)/10, ties = mean)$y. I'm just wondering if there i...

Full_Name: Tim Heaton Version: 2.8.1 OS: linux-gnu Submission from: (NULL) (143.167.4.162) Hi, In my version of R, the stats package splinefun code for fitting a Fritsch and Carlson monotonic spline does not guarantee a monotonic result. If two adjoining sections both have over/undershoot the way the resulting adjustment of alpha and beta is performed can give modified values which still do not satisfy the required constraints. I posed th...

...tore byte-code compiled functions, as we have no problems with R-3.1.3, but do see an "Error in fct(x) : byte code version mismatch" with R-devel SVNrev r70532. Background: Starting from several x-y grids, in the sysdata.rda file of RobAStRDA, we store the results of calls to approxfun/splinefun to these grids from within a session with pkg RobAStRDA require()d. From pkg RobExtremes we then call these interpolating functions by means of a call (essentially) as: getFromNamespace(".RMXE", ns = "RobAStRDA")[["GEVFamily"]][["fun.N"]][[1]](1.3) upon...

Hello, Is the an analogous function to splinefun or approxfun for multivariate data sets? For example, if I have a data set w/ x's and corresponding y's, I can use either splinefun or approx fun to find values of y for interpolated values of x. Now, what if I want to do the same thing except with a 3 dim. system? If I have a da...

...m Vf[,1] and y are taken from V[,1] respectively), because function apply() base on 1 argument I made it in this way: Vspline<-matrix(0,nrow=2*n,ncol=K) Vspline<-rbind(Vf[,1:3],V[,1:3]) where n=5000 and it is number of rows in V and Vf matrices and then: FV<-apply(Vspline,2, function(z) splinefun(Vspline[1:n,z],Vspline[(n+1):(2*n),z], method="mono",ties=mean)) The problems is, that when I am running it, following error occurs: Error in xy.coords(x, y) : only 0's may be mixed with negative subscripts I was trying to run function apply replacing z with particular values, and...

At present R has separate functions "spline" and "splinefun". The first of these carries out spline interpolation of a data set and returns the interpolated values; the second returns the interpolating function itself (approx and approxfun are similar). I would like to combine these into a single function "spline" with an (optional) argumen...

Has anyone got a function for smooth monotonic interpolation of a univariate function? I'm after something like the NAG function PCHIM which does monotonic Hermite interpolation. Alternatively, montononic cubic spline interpolation. Please reply directly. Rob Hyndman ___________________________________________________ Rob J Hyndman Associate Professor & Director of Consulting

...e no problems with R-3.1.3, but do see an "Error in fct(x) : byte code >> version mismatch" with R-devel SVNrev r70532. >> >> Background: >> Starting from several x-y grids, in the sysdata.rda file of RobAStRDA, we store the results >> of calls to approxfun/splinefun to these grids from within a session with pkg RobAStRDA >> require()d. From pkg RobExtremes we then call these interpolating functions by means of >> a call (essentially) as: >> >> getFromNamespace(".RMXE", ns = "RobAStRDA")[["GEVFamily"]][[&...

...unctions, as we have no problems with R-3.1.3, but do see an "Error in fct(x) : byte code > version mismatch" with R-devel SVNrev r70532. > > Background: > Starting from several x-y grids, in the sysdata.rda file of RobAStRDA, we store the results > of calls to approxfun/splinefun to these grids from within a session with pkg RobAStRDA > require()d. From pkg RobExtremes we then call these interpolating functions by means of > a call (essentially) as: > > getFromNamespace(".RMXE", ns = "RobAStRDA")[["GEVFamily"]][["fun.N&quot...

Dear All, I tried following for getting derivative of a polynomial in R i<- -10:10 x<-i*i*i+3*i*i+2 fun_spline<-splinefun(i,x) plot(x,type="l") lines(x,fx_spline(x, deriv=1), col='green') lines(x,fx_spline(x, deriv=2), col='green') Now when I plot 3*i*i + 6*i and 6*i + 6 the plot was not same for first deivative. where as the 2nd derivative was same Is this a correct method for getting deri...

...ction from a linear model. I think there should be build-in function that perform this action but I've had no luck finding it. For example, I have a model created using lm(). model <- lm(sat.d~1+sat.n+I(sat.n^2)) What I would like to have is a function (similar to the one generated by splinefun()) so that I can use it on different data-sets. Thanks in advance for the help. Tony Han Bao tonybao at mac.com

Hi folks: Is there a lookup function that returns the variate given the cumulative probability for an object returned by the density(...) function? > mydata _ as.vector(mymatrix) > mydata.density _ density(mydata) > mydata.p80 _ lookup(mydata.density, p=0.8) # is there any function to accomplish this task? Thanks. Rajiv. -------- Rajiv Prasad, Postdoctoral Research Associate,

--AZaLVt6Pw+ Content-Type: text/plain; charset=us-ascii Content-Description: message body text Content-Transfer-Encoding: 7bit Dear all, I was looking at "splinefun" and the underlying C code and believe that there is a memory access error in the C routine "spline_eval". Specifically, on line 368 and following the following code appears: if(ul < x[i] || x[i+1] < ul) { i = 0; j = *n; do { k = (i+j)/2; if(ul < x[k])...

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?