similar to: 3-dim splinefun?

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 with an x,y, and z? i have found the akima

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) argument which determines which

--MP_/Rxf/JAvsQx5JLkhZFc9Jmn4 Content-Type: text/plain; charset=US-ASCII Content-Transfer-Encoding: 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

--MP_/kvy20nVajVG/n.8m=_ZjLAX Content-Type: text/plain; charset=US-ASCII Content-Transfer-Encoding: 7bit Content-Disposition: inline On Tue, 7 Oct 2008 19:31:03 +0800 Berwin A Turlach <berwin at maths.uwa.edu.au> wrote: > The attached patch (against the current SVN version of R) implements > the latter strategy. With this patch applied, "make check > FORCE=FORCE" passes

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

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. I do not think this is due to finite precision

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 is something wrong with the package or if I'm doing

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 these points using

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 >

Can you provide a complete reproducible example? Sent from my iPhone > On May 1, 2016, at 6:51 AM, Peter Ruckdeschel <peter.ruckdeschel at web.de> wrote: > > Hi r-devels, > > we are seeing a new problem with our packages RobAStRDA (just new on CRAN, thanks > to Uwe and Kurt!) and RobExtremes (to be submitted). > > It must be something recent with the way you

I can't reproduce the more complex version. But the package on CRAN fails in the same way on 3.2.3 and 3.3.0. The problem is that your sysdata.rda includes a function that is generating this error. If you do f <- getFromNamespace(".RMXE", ns ="RobAStRDA")[["GEVFamily"]][["fun.N"]][[1]] g <- get("fct", environment(f)) and look at the

Hi r-devels, we are seeing a new problem with our packages RobAStRDA (just new on CRAN, thanks to Uwe and Kurt!) and RobExtremes (to be submitted). It must be something recent with the way you internally treat/store 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:

Thanks, Luke, for having a look to it. Sure, I can give you some reproducible example -- even in two degrees of completeness ;-): see below. Thanks again, Peter %----------------------------------- (I) first example %----------------------------------- Just to reproduce the error, on r-devel, try: install.packages("RobAStRDA") require(RobAStRDA) getFromNamespace(".RMXE", ns

Thanks to Ross Ihaka and Bob Wheeler for responding to my earlier question. I looked into the Johnson system functions in SuppDists package. For now, I want to stick with the density(...) estimator, and so still need the variate lookup function. As per Ross' suggestion, I just did a numerical integration on the density object and used approxfun/splinefun to "lookup" the variate

Hi all, I had the need to create a colorbar considering the alpha channel of the colors, but colorRamp() and colorRampPalette() ignored the alpha argument in rgb(). So I performed some minor modifs. in their codes, as to support the interpolation using the alpha channel. I guess that those simple modifications might be useful for other people, so perhaps it would be worth to add them to

A recent R devel NEWS item: approx(), spline(), splinefun() and approxfun() also work for long vectors. In current R devel, in function 'approx1' in src/library/stats/src/approx.c and in function 'spline_eval' in src/library/stats/splines.c, in #ifdef LONG_VECTOR_SUPPORT there is a comment "R_xlen_t is double". It is incorrect. In Rinternals.h, in #ifdef

Hello, I am struggling to overcome following problem: I have matrix Vf and matrix V, which both have 3 columns and I want to create a spline function basing on coordinates from this matrices (more precisely coordinates of function nr 1: x are taken from Vf[,1] and y are taken from V[,1] respectively), because function apply() base on 1 argument I made it in this way:

Hello, I am making some use of ROC curve analysis. I find much help on the mailing list, and I have used the Area Under the Curve (AUC) functions from the ROC function in the bioconductor project... http://www.bioconductor.org/repository/release1.5/package/Source/ ROC_1.0.13.tar.gz However, I read here... http://www.medcalc.be/manual/mpage06-13b.php "The 95% confidence interval for

Newbie question - mechanical engineer trying to learn R I've had success with plotting time series data and even made a heat map using R Graphs Cookbook by Mittal. I have a new problem - I need to align a number of time series data "columns" to the desired regular exact time stamp vector. The target time vector could be finer or more course than the typical time stamp spacing found.

I have now committed a version "fulfilling" your wish, partly at least, to R-devel . In the new approx(*, na.rm=FALSE) cases, the result of how NA's are treated does depend on the 4 different extrapolation rules {1, 2, 1:2, 2:1} The main reason was that I kept the low level code in C to do +- what it did before which automatically was using 'rule' to determine these