similar to: how to use print() without column names?

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! 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. --

Hello R'ers In previous versions of R (I now use 2.0.1) there was a package "bootstrap". I wrote some programs that depended heavily on this package but can unfortunately not find it on Cran today. Is there any way to find an older version of "bootstrap" and use it with the new version - 2.0.1? Sincerely Fredrik Lundgren Norrk??ping Sweden

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 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 found the need of converting a matrix into a list of its columns (for use with do.call), and was surprised there was no method as.list.matrix, it could easily be a part of as.list default I wrote my.as.list.matrix <- function(mat) { if(!is.matrix(mat))stop("Argument must be a matrix") n <- NCOL(mat) res <- vector(mode="list", length=n)

With rw2010dev I get a strange protect(): protection stack overflow error with a small data frame which otherwise is usable: If anybody wants to have a look I can provide an RData file with the problematic data frame. Doesn't seem to be necessary, the following simulated example generates the error: > testmat <- matrix(1:80, 20,4) > dim(testmat) [1] 20 4 > str(testmat) int

On trying with very smll test packages to try drilling down to som problems earlier reported in this list, I detected the following: R CMD check on a package with an R subdirectory empty, reports: * checking R files for syntax errors ... ERROR Syntax error in file On removing the empty subdirectory, the error disappears. Kjetil -- Kjetil Halvorsen. Peace is the most effective weapon of

Hi, Would you help me solve the following question? Thanks. Question: If I try to set the probability=0.05 and find the approximate x. (The answer should be somewhere between 2.1782 and 2.1783.) I write about this R program as follows but I don¡¦t know how to get the value of x which is between 2.1782 and 2.1783. library(mvtnorm) value<-array(1000) a<-array(1000)

Hello! I was reading R-intro and I have some suggestions: R-intro.html#A-sample-session rm(fm, fm1, lrf, x, dummy) suggestion rm(fm, fm1, lrf, x, y, w, dummy) The next section will look at data from the classical experiment of Michaelson and Morley to measure the speed of light. file.show("morley.tab") mm <- read.table("morley.tab") suggestion mm <- data(morley)

Dear List, We are planning a genotyping study to be analyzed using false discovery rates (FDRs) (See Storey and Tibshirani PNAS 2003; 100:9440-5). I am interested in learning if there is any consensus as to how many features (ie. how many P values) need to be studied before reasonably reliable FDRs can be derived. Does anyone know of a citation where this is discussed? Bill Dupont William D.

Hello, I am hoping someone can help me with the following multivariate issue: I have a model consisting of about 50 covariates. I would like to reduce this to about 5 covariate for the reduced model by combining cofactors that are strongly correlated. Is there a package or function that would help me with this in R? I appreciate any suggestions. Thanks, Ian

This is rw2010 from CRAN. When running Rcmd check on a package I get: Warning in utils::data(list = al, envir = data_env) : data set 'vowel.test' not found Warning in utils::data(list = al, envir = data_env) : data set 'vowel.train' not found Warning in utils::data(list = al, envir = data_env) : data set 'waveform.test' not found Warning in utils::data(list

This is rw2010 from CRAN. When running Rcmd check on a package I get: Warning in utils::data(list = al, envir = data_env) : data set 'vowel.test' not found Warning in utils::data(list = al, envir = data_env) : data set 'vowel.train' not found Warning in utils::data(list = al, envir = data_env) : data set 'waveform.test' not found Warning in utils::data(list

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

Try this: > ?convolve > x<-rnorm(1000) > y<-rep(1,20) > z<-convolve(x,y,type="filter") > plot(x,type="l") > str(z) num [1:981] 6.31 7.28 8.16 7.39 4.65 ... > lines(c(rep(0,10),z,rep(0,10)),col="yellow",lwd=3) > lines(c(rep(0,10),z,rep(0,10))/length(y),col="red",lwd=3) #running mean You wrote: Does anyone know an easy way

What is the difference between arima and arima0?

Dear R list members, Please excuse my ignorance but as a new comer to R I was wondering if anyone knows of any functions in R or Splus that can test a time-series for non-stationarity such as the Pettitt or the Mann-Kendall tests. Kind regards, Jon Nott [[alternative HTML version deleted]]

I am trying to find out if someone has implemented a (McFadden-type) multivariate binary logistic regresssion package for R? From what I can tell, this is not available for R. Thank you, Lynne Baker [[alternative HTML version deleted]]

i tried to use df(x,df1,df2) but the values arent the same when i looked it up in a F Distribution table.. How to get the same F Distribution values in R as in the f table?