similar to: Help needed

Hello I am trying to solve these problems and I am not allowed to use loops or ifs. 1st Question My first question is that I have generated 100 random numbers from the uniform distribution then A)add only the negative integers. B)add elements until the first appearance of a negative element. I know how to choose the negative elements for A but how to find integers? And I dont know what to do

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

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

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]]

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 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="",

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

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

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 <-

Hello How come that the function md.pattern() from package 'mice' delivers a warning when run over data sets with more than 31 variables? library( 'mice' ) x <- as.data.frame( matrix( sample( c(1:3, 1:3, 1:3, NA), 7000, repl=TRUE ), ncol=35, dimnames=list(NULL, paste('V', 11:45, sep="") ) ) ) md.pattern(x) # Warning message:

Hello Hello I have a data frame, x, holding 5 persons answering the question which cars they have used: # the data frame x <- as.data.frame( matrix( c('BMW', '', '', 'Mercedes', 'VW', '', 'Skoda', 'VW', 'BMW', '', '', '', 'VW', 'Skoda',

Hello R users I am quite new to bootstrapping. Now, having some data x, ---- R: set.seed(1234) R: x <- runif(300) ---- I want to bootstrap simple statistics, mean and quantiles (.025, .975). Currently, I run a loop ---- R: res <- as.data.frame(matrix(ncol = 3, dimnames = list(NULL, ... c("M", "Lo", "Hi")))) R: for (i in 1:100) { ... y <-

I am looping through various models with different combinations of independent variables which are stored as columns in x glm(y ~ ??, data=x) How can I pass the colnames of the selected columns of x into ?? seperating them with a + ie I want to generate glm(y ~ x1 + x2, data=x) glm(y ~ x2 + x3, data=x) glm(y ~ x1 + x2 + x4, data=x) ... I have tried the sedit function

I'm preparing to submit my first package to CRAN, thanks to the help of too many people to mention. I've built and checked the package on Windows ( making a zip) and my path points to the 64 bit version of R. Everything builds and checks and the final warnings have been fixed. My package is pure R with no source from other languages. My questions are as follows. I've read the

how do I create a data frame with the given column names _NOT KNOWN IN ADVANCE_? i.e., I have a vector of strings for names and I want to get an _EMPTY_ data frame with these column names. is it at all possible? -- Sam Steingold (http://sds.podval.org/) on CentOS release 5.3 (Final) http://openvotingconsortium.org http://pmw.org.il http://memri.org http://mideasttruth.com

There is a code from SPSS Syntax do if sub(ATVK,2,2)="01". comp strata=1. else if sub(ATVK,2,2)>="05" and sub(ATVK,2,2)<="27". comp strata=3. else if sub(ATVK,4,2)>"20" or sub(ATVK,6,2)>"20". comp strata=4. else if sub(ATVK,4,2)>"00". comp strata=2. end if. value labels strata 1 "R 2 "Li" 3 "M" 4

Dear listserv, Here is my latest formatting problem. I would like to rotate the x-axis labels by 45 degrees on a _barplot_. Apparently this is slightly different from the example given in the R FAQ, which is for rotating the x-axis labels on a scatterplot (http://cran.r-project.org/doc/FAQ/R-FAQ.html#How-can-I-create-rotated-axis-labels_003f). I have adapted that code, as best I could, and

Hello, I am working with a dataset which essentially has only one column - a list of distances in metres, accurate to several decimal places. eg distance 1000 6403.124 1000 1414.214 1414.214 1000 I want to organise this into a frequency table, grouping into categories of 0 - 999, 1000 - 1999, 2000-2999 etc. I'd also like the rows where there are no data points in that category to

Hello R experts I am googling and reading around, however, I can't get it working (perhaps because I do not understand much C, however, I'll give it a try). I am trying to include C++ code into an R routine, where the C++ code looks: #include <iostream> using namespace std; void foo (double* x, double* y, double* out) { out[0] = x[0] + y[0]; } Back in R, the command R CMD