similar to: Using combn

Hi, i am working on a problem where i need to compute the products of all possible combinations of size m of the elements of a vector. I know that this can be achieved using the function combn(), e.g.: > vector <- 1:6 > combn(x = vector, m = 3, FUN = function(y) prod(y)) In my case the vector has 2000 elements and i need to compute the values specified above for m = 32. Using combn() i

Dear All, I have a dataframe made up of individual beetles consisting of individual number, family number, mother's family number, father's family number, and sex of the beetle. I would like to pair up the individuals for breeding. I would, however, like to avoid breeding beetles of the same sex (obviously), the same family, and with the same mother's family or father's family,

Dear list, I have come across this issue: combn(letters[1:5], 3) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c" [2,] "b" "b" "b" "c" "c" "d" "c"

This is a 'rather than re-invent the wheel' post. Has anyone out there re-written combn so that it can be parallelized - with multicore, snow, or otherwise? I have a job that requires large numbers of combinations, and rather than get all of the index values, then crank it through mclapply, I was wondering if there was a way to just do this natively within a function. Just curious.

It seems people are reinventing the wheel here: The goal is to generate all combinations of 1:n of size k. This (typically) results in a matrix of size k * choose(n,k) i.e. needs O(n ^ k) space, hence is only applicable to relatively small k. Then alternatives have been devised to generate the combinations "one by one", and I think I remember there has been a quiz/challenge about 20

Hello! I've a problem with the combn function and a set of vector. I would like to make a simple combination where, instead of scalars, i would like to combine vector, in order to form matrixes. In other words, i have nineteen 6-items vectors (for example coef1-coef19), that i would like to combine in n!/k!(n-k)! 6x6 matrixes. I tried with a code like this mma <-

I'm able to do this as follows, but am wondering if anyone knows a simpler way which still avoids explicit loops? > (mystring <- letters[1:5]) [1] "a" "b" "c" "d" "e" > unlist(sapply(mystring[-length(mystring)], + function(x) paste(x,mystring[(grep(x,mystring)+1):length(mystring)],sep=""))) a1 a2 a3

http://www.nabble.com/file/p15359204/test.data.csv http://www.nabble.com/file/p15359204/test.data.csv test.data.csv Hi, I have used apply to have certian combinations, but when I try to use these combinations I get the error [Error in eval(expr, envir, enclos) : object "X.GDAXI" not found]. being a novice I donot understand that after applying combination to the data I cant access

Hi The message occurred from R, when I was selected of "optimization > block diagonal Fhiser matrix" and used the attached file on PFIM. Could you please advise me about the following message? ***************************** Loading required pakage: combinat Attaching package:'combinat' The following object(s) are masked from 'package:utils':combn

Hello, I have got the following problem: > setwd("C:/temp") > library(xlsReadWrite) > MyData <- read.xls(file="Mappe1.xls", colNames = TRUE,dateTimeAs = "isodatetime") > attach(MyData) > MyData name value times 1 A1 2 2006-05-12 2 A2 3 2006-05-16 3 A3 1 2006-05-12 4 A4 4 2006-05-12 5 A5 2

Dear list, # I have a DF like this: sleep$b <- c(rep(8,10), rep(9,10)) sleep$me <- with(sleep, ave(extra, group, FUN = mean)) sleep # I would like to create a new variable # holding the b-th value of group 1 and 2. # This is not what I want, it takes always the '8' from group '1' # and not the '9' sleep$gr <- with(sleep, ave(extra, group, FUN = function(x)

General problem: I have 20 projects that can be invested in and I need to decide which combinations meet a certain set of standards. The total possible combinations comes out to 2^20. However I know for a fact that the number of projects must be greater than 5 and less than 13. So far the the code below is the best I can come up with for iteratively creating a set to check against my set of

Hello All, I have just installed my R 2.4 (windows) as a test trying to load a data frame and run combn() for each line into another file. How do I do this? data.csv: a,b,c,d 1,2,3.4 g,3,6,t etc x=data.csv, m=3 Thank you Zam _________________________________________________________________________________ This email contains confidential information intended only for the person named

Hi, I was checking the source code to the function combn that "generates all combinations of the elements of 'x' taken 'm' at a time.", because I wished to modify it. I have a doubt about a statement. This is the main loop. ._1 <- 1:1 nmmp1 <- n - m + ._1 while (a[1] != nmmp1) { if (e < n - h) { h <- ._1 e <-

Hi, I'm trying to conduct sensitivity analysis in R using the 'sensitivity' package. Although the description of functions seem straightforward, I can?t succeed. The definition of input factors can be the problem. library(sensitivity) #A simple model with 4 input factor to test the morris function: model01=function(a1,a2,a3,a4) { Z<-numeric(10) Z[1]<-runif(1)

Hello, I'm new in R and I want to do one thing that is very easy in excel, however, I cant do it in R. Suppose we have the data frame: data<- data.frame(A=c("a1","a2","a3","a4","a5")) I need to obtain another column in the same data frame (lets say B=c(b1,b2,b3,b4,b5) in the following way: b1=a1/(a1+a2+a3+a4+a5)

Dear User, thank for the attention. I have a data.frame with 5 columns (ex:ID, a1,a2,a3,a4) and 1000 rows. I wish to find the absolute max value for all data.frame and save a new data.frame with the row where is that value. Ex: ID: 1,2,3,4,5,6,7,8,9,10 a1:1,2,3,4,5,6,7,8,9,10 a2:11,12,13,14,15,16,17,18,19,20 a3:21,22,23,24,25,26,27,28,29,30 a4:31,32,33,34,35,36,37,38,39,40 The

Dear R users, Basically, from the following arbitrary data set: a <- data.frame(id=c(c("A1","A2","A3","A4","A5"),c("A3","A2","A3","A4","A5")),loc=c("B1","B2","B3","B4","B5"),clm=c(rep(("General"),6),rep("Life",4))) > a

Dear colleagues, I'd like to reshape a datafame in a long format to a wide format, but I do not quite get what I want. Here is an example of the data I've have (dat): sp <- c("a", "a", "a", "a", "b", "b", "b", "c", "d", "d", "d", "d") tr <- c("A",

Dear All, Here is a hypothetical sample (sorry for the clumsy code): A1 <- matrix(1:5, nrow=5, ncol=1) A2 <- matrix(6:10, nrow=5, ncol=1) A3 <- matrix(11:15, nrow=5, ncol=1) A4 <- matrix(16:20, nrow=5, ncol=1) A5 <- matrix(21:25, nrow=5, ncol=1) A6 <- matrix(26:30, nrow=5, ncol=1) B1 <- matrix(c(A1, A2, A3), nrow=5, ncol=3) B2 <- matrix(c(A2, A3, A4), nrow=5, ncol=3) B3