similar to: boot() versus loop, and statistics option

Tinn-R (http://www.sciviews.org/Tinn-R/) is one of the topmost suggestions when googling an R-(text-)editor for Windows. However, to me it appears dissappointing that Tinn-R does not handle utf-8 (mac-roman, or any other) encoded R-scripts or, in general, text files. Besides Emacs and the R built-in editor, could you recommend a good editor for Windows, even some commmercial for a small

Hello, I am looking for an elegant one-liner for the following operation: x <- rnorm(10) y <- runif(10) c(mean(x)-mean(y), mean(x)+mean(y)) I thought about apply(data.frame(x, y), 2, mean) but I don't know how to apply the +- operation on the result of apply. Thanks, *S* -- Sascha Vieweg, saschaview at gmail.com

Some attribute x from 17 individuals was recorded repeatedly on 6 time points using a Likert scale with 7 distractors. Which statistical test(s) can I apply to check whether the changes along the 6 time points were significant? set.seed( 123 ) x <- matrix( sample( 1:7, 17*6, repl=T ), nrow = 17, byrow = TRUE, dimnames = list(1:17, paste( 'T', 1:6, sep='' )) ) I found

Hello, Vector y is an alphabetically sorted version of vector x. Will both samples, X and Y, be "absolutely" random or will they have systematic differences? And: Should I sort or shuffle a vector before sampling? Thank you, *S* x <- as.factor(LETTERS[sequence(10:1)]) y <- sort(x) X <- sample(x, 5) Y <- sample(y, 5) -- Sascha Vieweg, saschaview at gmail.com

Hello Currently, I plot some coefficients with some intervals using function "plotCI()" (package "gplots") using the following code: (m1 <- matrix(0:5, nrow=2, byrow=T, dimnames=list(c("v1", "v2"), c("lo", "m", "hi")))) m2 <- m1 + 1 library(gplots) plotCI( x=1:length(m1[, 1]), pch="",

Hi there, I have a numeric vector let say: Vect <- c(12.234, 234.5675, 1.5) Now I want a string vector like: changedVec <- c("012.234", "234.568", "001.500") Would be grateful if somebody help me how can I do that. Thanks and regards, [[alternative HTML version deleted]]

Running a binary logit model on the data df <- data.frame(y=sample(letters[1:3], 100, repl=T), x=rnorm(100)) reveals some residual deviance: summary(glm(y ~ ., data=df, family=binomial("logit"))) However, running a multinomial model on that data (multinom, nnet) reveals a residual deviance: summary(multinom(y ~ ., data=df)) On page 203, the MASS book says that "here the

Hello How can I apply functions along "layers" of a data matrix? Example: daf <- data.frame( 'id' = rep(1:5, 3), matrix(1:60, nrow=15, dimnames=list( NULL, paste('v', 1:4, sep='') )), rep = rep(1:3, each=5) ) The data frame "daf" contains 3 repetitions/layers (rep) of 4 variables of 5 persons (id). For some reason, I want to calculate

Hello, If the signature of a method defines which generic it implements then I'm confused about why this minimal example I invented won't work : setGeneric("myFun", function(rs, ...){standardGeneric("myFun")}) setGeneric("myFun", function(cs, ...){standardGeneric("myFun")}) setMethod("myFun", "numeric", function(rs, colour =

I declared the environment of the function myfun to be NULL as follows: environment(myfun) <- NULL Later on I called that myfun and got an error message because the function index() in the zoo package was called inside myfun and was not visible: Error in myfun(args) : couldn't find function "index" I tried to use zoo::index() instead of index(), but that did not work. In fact,

Dear Rers, I have a function to barplot() a matrix, eg myfun <- function(x, ...) { barplot(x , ... )} (The real function is more complicated, it does things to the matrix first.) So I can do: m1 <- matrix(1:20,4) myfun(m1) myfun(m1, main="My title") I'd like to be able to add the number of rows of the matrix passed to the function to the "..." argument, eg

Hello R users, i'm wondering how to trigger variable creation. Whenever a variable is created i want my own function myFun(...) to be started. if (exists("x")) {rm(x)} # after removal of x # any of these calls x<-10 # should call myFun x=10 # should call myFun assign(x,10) # should call myFun etc.

I run a multinomial regression on a data set with an outcome that has three values. First, I build an initial model, b.mod. Then I run a loop to bootstrap the coefficients. For the initial model, using "predict()", I can print the wrong/false predictions table. But how do I get this table (that is, the predictions) for the bootstrapped model? Thanks for hints, *S* df <-

Of course (and unsurprisingly) Duncan is correct. I see that behavior in R 3.1.0, as well as the modern ones Duncan mentioned. What I said is true, as far as it goes, but the symbol being resolved is FUN, so when looking for a function it doesn't find the function version of round. Did you perhaps have a function named FUN in your global environment? If so you are being bitten by what I

R> myfun <- function(x, ...) {x[...] <- 0; x} R> myfun(3) Error in myfun(3) : SubAssignArgs: invalid number of arguments It fails because no ... was passed. The workaround (and desired behavior) is: R> myfun <- function(x, ...) {if (missing(...)) x[] <- 0 else x[...] <- 0; x} R> myfun(3) [1] 0 Deja vu? This is the one piece of my PR#1110 (Oct 3, 2001) that I

Is there a way to call a function, and explicitly set an argument to 'not specified'? My situation is the following. I have a function which passes on most of its arguments to another function. The second function, myfun2, serializes all arguments and is out of my control. myfun <- function(...){ return(myfun2(...)); } now, the value for arguments of myfun are stored in variables.

Hi, on R version 2.15.1 (2012-06-22) (Platform: i686-pc-linux-gnu (32-bit)) sourced functions have srcref attached as an attribute. Are such data also available for S4 generics and methods? How? (See sample code below) Thank you. Bests, Renaud f <- textConnection( " f <- function(){} setGeneric('myfun', function(x, ...) standardGeneric('myfun'))

Hi, this is a made-up example. Function "myfun" returns two arguments. Can "apply" be used so that "myfun" is called only once? Thanks Serguei mat<-matrix(runif(50),nrow=10,ncol=5) myfun<-function(x) { mymean<-mean(x) mysd<-sd(x) return(mymean,mysd) } out1<-t(apply(mat,1,function(x) myfun(x)$mymean)) out2<-t(apply(mat,1,function(x)

Hi, I have a function myFun which I want to call multiple times, using different argument lists. myFun("v1", "2009", 1) myFun("v2", "2008", 1) myFun("q", "2001") How can I easily do this in R? Should I use mapply? I unsuccessfully tried something like: x <- list(c("v1", "2009", 1), c("v2",

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Michael > Sent: Thursday, April 20, 2006 3:50 AM > To: R-help at stat.math.ethz.ch > Subject: [R] Bootstrap error message: Error in > statistic(data, original, ...) : unused argument(s) ( ...) [Broadcast] > > > Dear colleagues, >