similar to: how to view the top 20 lines in a long dataset

Hi, I am trying to use xyplot to plot the relationship between size and day (y~x) by a food factor that has two levels, low and high. I have 3 reps per factor/day. I want the plots from each food treatment on the same axiss, so I used this code: xyplot(Size ~ Day, groups = Food, data = louis.data.means,col=1, pch=c(1,17), panel=function(x,y,groups,...){ panel.superpose(x,y,groups,...)

Hi, I have a number of genes (columns) for which I want to examine pairwise associations of genotypes (each row is an individual)...For example (see data below), I would like to compare M1 to M2, M2 to M3, and M1 to M3 (i.e. does ac from M1 tend to be found with bc from M2 more often than expected.) Down stream I will be performing chi square tests for each pair. But I am looking for a way to

Hello all, I am trying to create a matrix of 1s and -1s without any repetitions for a specified number of columns. e.g. 1s and -1s for 3 columns can be done uniquely in 2^3 ways. -1 -1 -1 -1 -1 1 -1 1 -1 -1 1 1 1 -1 -1 1 -1 1 1 1 -1 1 1 1 and for 4 columns in 2^4 ways and so on. I finally used the function combn([0 1],3) that I found at the following link

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, 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

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]] =

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 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

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

Hi Folks, Given a series of n independent Bernoulli trials with outcomes Yi (i=1...n) and Prob[Yi = 1] = Pi, I want P = Prob[sum(Yi) = r] (r = 0,1,...,n) I can certainly find a way to do it: Let p be the vector c(P1,P2,...,Pn). The cases r=0 and r=n are trivial (and also are exceptions for the following routine). For a given value of r in (1:(n-1)), library(combinat) Set <- (1:n)

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$Species)[i] tmp

Dear R-helpers, I'm trying to develop a function which specifies all possible expressions that can be formed using a certain number of variables. For example, with three variables A, B and C we can have - presence/absence of A; B and C - presence/absence of combinations of two of them - presence/absence of all three A B C 1 0 2 1 3 0 4 1 5 0 6 1

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

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.

Hello I apologise for the length of this entry but please bear with me. In short: I need a way of subsampling communities from all possible communities of n taxa taken 1:n at a time without having to calculate all possible combinations (because this gives me a memory error - using combn() or expand.grid() at least). Does anyone know of a function? Or can you help me edit the combn or

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 <-

Hi I have very simple issue as I am still new to the group of R I have basically vector of names for which i want to create mutliple combinations and then place them in different vectors. In some other language I can just place a third dimension to separate list (or matrix) but i do not know how to do it in R. My issue is simple I use cc<-combn(colnames(DD),2) I would need to have this

Dear list, I want to apply the "table" function to every pair of variables in df and the return should be a list. setwd(123) asd <- data.frame(a1=sample(1:4, 20, 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,

Respected All, I hope you are enjoying good health, I am tring to write a program in R but could not be very sucessful. My program draws random sample form bivariate normal distribution and then compute a variable PIJ. For certian samples some entries of variable PIJ is apearing as negative, which result in negative variance estimator. I want to introduce a loop in my program that verify the each