similar to: seq(along= surprise

Hola! I am sending this to the list since emails from me to Simon Wood has bounced earlier. I get: > library(tsDyn) Loading required package: mgcv Erro en `parent.env<-`(`*tmp*`, value = NULL) : use of NULL environment is defunct Error: package 'mgcv' could not be loaded > library(mgcv) Erro en `parent.env<-`(`*tmp*`, value = NULL) : use of NULL environment

Hola! Este mail llegó a r-help hoy, yo lo mandó también a esta lista. Es interesante con competiciones de predicción/clasificación! ¿Alguien que quiere cooperar? Kjetil ---------- Forwarded message ---------- From: Kjetil Halvorsen <kjetilbrinchmannhalvorsen@gmail.com> Date: Fri, Jan 29, 2010 at 12:19 Subject: Fwd: [R] Classification of supernovae - a challenge To: Kjetil Halvorsen

I am experimenting with rSymPy, and it seems to work nice. However, I dislike the need to wrap all sympy expressions within quotes, it leads to ugly calls like library(rSymPy) Var("x,y,z") sympy("(x+y)**2") and so on. Inspired by the function cq from mvbutiles package: library(mvbutils) > cq function (...) { as.character(sapply(as.list(match.call(expand.dots =

I am trying to use KalmanSmooth to smooth a time series fitted by arima (and with missing values), but the $smooth component of the output baffles me. Look at the following example: testts <- arima.sim(list(ar=0.9),n=100) testts[6:14] <- NA testmod <- arima(testts, c(1,0,0)) testsmooth <- KalmanSmooth(testts, testmod$model) par(mfrow=c(2,1)) plot(testsmooth$smooth,

Your understanding isn't similar to mine. Mine says robust/resistant methods are for data with heavy tails, not heteroscedasticity. The common ways to approach heteroscedasticity are transformation and weighting. The first is easy and usually quite effective for dose-response data. The second is not much harder. Both can be done in R with nls(). Andy From: Quin Wills > > I am

Hola! I am working on a problem where data points are (square) matrices. Is there a way to make a "vector" of matrices, such that it can be stored in a data.frame? Can that be done with S3? or do I have to learn S4 objects & methods? Kjetil

Hola! I have the following in a .Rd file: \eqn{\mbox{coef} = c(\mbox{coef}[1],\ldots, \mbox{coef}[n]) } {coef = c(coef[1], coef[2], \dots, coef[n])} However, both arguments come out in the latex file! Whats happening? Kjetil Halvorsen

Hola! I just changed my laptop to debian squeeze, downloaded R devel from svn repo, as described in the manual. Then I configured for building in a separate build dir with: kjetil at kjetil:~/R/Rbuilddir$ sudo ../svn/configure --- which succeeded, with: R is now configured for x86_64-unknown-linux-gnu Source directory: ../svn Installation directory: /usr/local C

Hola! I ask here since I learnt from this list that the LaTeX package listings should be good for typesetting R code. I encountered one problem: \begin{lstlisting} X %*% V \end{lstlisting} in the output the * in %*% disappears! same with %/%, etc, the / disappears. Any ideas? Kjetil -- Kjetil Halvorsen. Peace is the most effective weapon of mass construction. --

Have I been sleeping in class? rw1071 from CRAN, windows XP incidencia is made by a call to tapply > class(incidencia) [1] "array" > incidencia <- unclass(incidencia) > class(incidencia) [1] "array" Kjetil Halvorsen

Suppose I have x<-data.frame(v1=1:4, v2=c(2,4,NA,7), v3=rep(1,4), v4=LETTERS[1:4],v5=rep('Z',4)) or a much larger frame, and I wish to test for and remove the constant numeric columns. I made: is.constant<-function(x){identical(min(x),max(x))} and apply(x,2,is.constant) # Works for numerics x[,-which(apply(x,2,is.constant))] I'd really like to be able to

Hola! The R FAQ says: 7.12 How do I convert factors to numeric? It may happen that when reading numeric data into R (usually, when reading in a file), they come in as factors. If f is such a factor object, you can use as.numeric(as.character(f)) to get the numbers back. More efficient, but harder to remember, is as.numeric(levels(f))[as.integer(f)] In any case, do not call as.numeric()

Hello, I would like to know if there is an R-package available for computing the density, distribution function, quantiles and random numbers of the p-generalized normal distribution or if somebody is already working on it. Best regards, Steve Kalke

I'm trying to (re)learn Sweave and run into some problems. I use now ubuntu (8.10), emacs + ess. Slowly getting upto speed on ess. I have a complete (hopefully) .Rnw file, but the resulting .tex will not compile. The file does not contain anything exotic, but it produces pdf figures, and that is where the problems come: library(tools) > Sweave("varioCoo.Rnw") Writing to file

Hola! I will want to identify pixels in an image with the mouse, for so getting the image data from the matrix(es), for use in subsequent discriminant analysis. But the following bombs R: (windows XP, rw1071) > str(baboon) list() - attr(*, "size")= int [1:2] 512 512 - attr(*, "cellres")= num [1:2] 1 1 - attr(*, "bbox")= num [1:4] 0 0 512 512 - attr(*,

Using the heatmap function in mva, it seems to be hard to use different colors in the edges leading to different groups of objects, as commonly done in many heatmaps in the microarray graphics. Any suggestions? Thanks. max

I just discovered that when the VGAM package (not on CRAN) is loaded, glm() doesn't work. This is because VGAM defines a family function() which gets found by glm() in place of the family function from stats. Then VGAM:::family returns an object which doesn't have a $family component, (it has a component $vfamily). I thought namespaces should protect us from this happening? Kjetil --

I am trying to source a file defining a dataset, giving the full path. (rw1031 on windows 98) > source("c:\\kjetil\\audiometria\\data\\audiometria.R") Error in parse(file, n, text, prompt) : syntax error on line 6 also: > parse(file="c:\\kjetil\\audiometria\\data\\audiometria.R", n=-1) Error in parse(file, n, text, prompt) : syntax error on line 6 This seems very

Hi all, I'm looking for smooth monotone estimation packages, preferably using splines. I downloaded the 'cobs' package and intend to use it, but since it offers only quadratic splines based on L1 minimization, I'd like to compare its performance to that of a more 'mainstream' cubic-spline, L2-norm minimizing spline. Preferably a smoothing spline. Does anyone know of such

I am trying to install a local package and get this unexpected error: ---------- Making package UMSA ------------ adding build stamp to DESCRIPTION installing R files installing data files installing man source files installing indices Error: couldn't find function "na.omit" Execution halted na.omit of course is in package stats, and that is listed in the Depends field in