similar to: Bug or failing understanding?

I'm trying to write a formula method for canonical correlation analysis, that could be called similarly to lm() for a multivariate response: cancor(cbind(y1,y2,y3) ~ x1+x2+x3+x4, data=, ...) or perhaps more naturally, cancor(cbind(y1,y2,y3) ~ cbind(x1,x2,x3,x4), data=, ...) I've adapted the code from lm() to my case, but in this situation, it doesn't make sense to include an

The following I do not understand, but then I did'nt really use S4 methods ... > showMethods(plot) Function: plot (package graphics) x="ANY" x="lmList.confint" x="merMCMC" (inherited from: x="ANY") > plot(x=moda0MCMC) Error in as.double(y) : cannot coerce type 'S4' to vector of type 'double' > class(moda0MCMC) [1]

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 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. --

Hi, can somebody tell me why R is not able to calculate a linear model written in this way? > lm (seq(1:100)~seq(1:100)) Call: lm(formula = seq(1:100) ~ seq(1:100)) Coefficients: (Intercept) 50.5 Warning messages: 1: In model.matrix.default(mt, mf, contrasts) : the response appeared on the right-hand side and was dropped 2: In model.matrix.default(mt, mf, contrasts) : problem

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

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()

Dear R-users, I have an outcome variable and I'm unsure about how to treat it. Any advice? I have spending data for each county in the state of California (N=58). Each county has been allocated money to spend on any one of the following four categories: A, B, C, and D. Each county may spend the money in any way they see fit. This also means that the county need not spend all the money that

It is unclear to me how aov() handles non-categorical variables. I mean it works and produces results that I would expect, but I was under impression that ANOVA is only defined for categorical variables. In addition, help(aov) says that it "call to 'lm' for each stratum", which I presume means that it calls to lm() for every group of the categorical variable, however I

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

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 --

To whom it may concern, I happened to run the following R code just to check the layout of the output, but found that the code doesn't work the way I thought it should work. '' > lm(rnorm(100) ~ rnorm(100)) Call: lm(formula = rnorm(100) ~ rnorm(100)) Coefficients: (Intercept) -0.07966 Warning messages: 1: In model.matrix.default(mt, mf, contrasts) : the response appeared

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

I encountered something strange with read.spss (package foreign, version 0.7 with R2.0.0 and version 0.8 with R2.0.1 beta, windows XP) I made a test file test.sav with SPSS version 11.5.1 containing only one numeric variable, with a value label for one value not occuring in the file. According to ?read.spss this should result in a factor, but it results in all NA. Using the argument