search for: 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 encounter problems for m >= 4. Is there any alternative to combn() that works more effici...

...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, to avoid inbreeding. The pairs of the beetles can be done with the function combn(individual, 2). I have been trying to use the FUN argument of combn by reducing the options for combn for each individual by negating the rows that share the same sex, family, and parents' families, but I have had no success. Is there an easy way to package all of this into a function for the...

I've created a .Rd file (below), then converted that to .sgml using R CMD Rdconv --type=Ssgm combn.Rd > combn.sgml The output (shown below) is missing some of the sections: arguments seealso examples If instead I convert to .d (below), the same sections are missing, and the "note" section is included but without the necessary newline. -------------------------------------------...

Hi, anyone interested in this: I tried to simply this loop with lapply or something but haven't figured it out: mapt = c("203929_s_at", "203930_s_at", "203928_x_at", "206401_s_at") mapt.combn <- lapply(1:4, function(i) combn(mapt, i)) out = list() k = 1 for (i in 1:length(mapt.combn)){ for (j in 1:ncol(mapt.combn[[i]])){ out[[k]] = mapt.combn[[i]][,j] k = k + 1 } } out # the following two lines create a list of list, which is not my intended: y0 = mapt.combn lapply(1:4, func...

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" &quot...

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....

Ny understanding was that Insightful had been asked to provide patches fo this. We look forward to receiving them. On Tue, 10 Apr 2007, timh at insightful.com wrote: > I've created a .Rd file (below), then converted that to .sgml using > R CMD Rdconv --type=Ssgm combn.Rd > combn.sgml > The output (shown below) is missing some of the sections: > arguments > seealso > examples > If instead I convert to .d (below), the same sections are missing, > and the "note" section is included but without the necessary newline. > > ----...

Hi List, I'm hoping to get opinions for enhancing the efficiency of the following code designed to take a vector of probabilities (outcomes) and calculate a union of the probability space. As part of the union calculation, combn() must be used, which returns a matrix, and the parallelized version of lapply() provided in the multicore package requires a list. I've found that parallelization is very necessary for vectors of outcomes greater in length than about 10 or 15 elements, which is why I need to make use of multic...

...EVISED: 10 July 1995 # AUTHOR: Scott Chasalow OTOH, people have since reinvented the wheel quite prolifically: There's combinations() in gtools {based on Bill Venables' code from R News 1/1}, combs() in CAtools, subsets() in BHH2, and nchoosek() in vsn (bioconductor); then 'fwd.combn' in package "forward" which states explicitly that it is Scott's combn() renamed.. I stopped searching for more, and I've made sure all these 6 functions compute the same thing, at least in the most simple case. After simply replacing nCm() by choose(), and some other minor t...

Dear developeRs, I encounter the following problem: in the current version of my package FrF2, certain calls to a functioni do not work when package combinat is loaded, because function combn from combinat masks the function from utils that my package uses. I tried to solve this issue by importing function combn into the namespace of FrF2; I don't need to export it, I just want to use it internally in the package; I could of course find all occurrences and replace them with util...

...replace=TRUE), a2=sample(1:4, 20, replace=TRUE), a3=sample(1:4, 20, replace=TRUE), a4=sample(1:4, 20, replace=TRUE)) with(asd, table(a1, a2)) with(asd, table(a1, a3)) with(asd, table(a1, a4)) ... I'm sure there is a solution using "combn" - but I don't get it... combn(colnames(asd), 2) ... Thanks for any help! Patrick

...> 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 ***************************** Kind regards, Fumie

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...

Dear all, I want to apply a function to list elements, two by two. I hoped that combn would help me out, but I can't get it to work. A nested for-loop works, but seems highly inefficient when you have large lists. Is there a more efficient way of approaching this? # Make some toy data data(iris) test <- vector("list",3) for (i in 1:3){ x <- levels(iris$Speci...

On Tue, 10 Apr 2007 timh at insightful.com wrote: > I've created a .Rd file (below), then converted that to .sgml using > R CMD Rdconv --type=Ssgm combn.Rd > combn.sgml > The output (shown below) is missing some of the sections: > arguments > seealso > examples > If instead I convert to .d (below), the same sections are missing, > and the "note" section is included but without the necessary newline. The underlyin...

...")# read it in matrix format #fruit =read.file(row.names=1)$data mD =head(fruit[, 1:5])# only first five used in combinations #X.SSMII = head(fruit[, 6])# Keep it for referebce nmax = NULL n = ncol(mD)# dont take the last column for reference purpose if(is.null(nmax)) nmax = n mDD = apply(combn(5, 1),1, FUN= function(y) mD[, y])# to fg = lm( X.SSMII ~ X.GDAXI + X.FTSE + X.FCHI + X.IBEX, data = mDD )# regress on combos s = cbind(s, Residuals = residuals(fg))# take residuals print(mD) -- View this message in context: http://www.nabble.com/Applying-lm-to-data-with-combn-tp15359204p1...

I have been struggling trying to write some code to produce all combinations subject to some restrictions. I thought someone might have some bright ideas. I have 11 values which fall into 5 groups. I want all combinations of 2,3, and 4 values where each value must be from a different group. The numbers in the groups are different. Here is a definition of the groups: groups <- list(gp1 =

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 above an...

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) {...

..."all.expr" <- function(column.names) { ncolumns <- length(column.names) return.matrix <- matrix(NA, nrow=(3^ncolumns - 1), ncol=ncolumns) colnames(return.matrix) <- column.names rownames(return.matrix) <- 1:nrow(return.matrix) start.row <- 1 all.combn <- sapply(1:ncolumns, function(idx) { as.matrix(combn(ncolumns, idx)) }, simplify=FALSE) for (j in 1:length(all.combn)) { idk <- all.combn[[j]] tt <- matrix(NA, ncol=nrow(idk), nrow=2^nrow(idk))...