similar to: Most often pairs of chars across grouping variable

Hi, we're using Samba 3.5.6 (Debian). Windows 7 clients often create new roaming profiles for existing users for no identifiable reason. Windows XP isn't affected. Is this a known problem? - Chris

All, I am looking at an example in Aliaga's Interactive Statistics. Bag A has the following vouchers. BagA <- c(-1000,10,10,10,10,10,10, 10,20,20,20,20,20,20,30, 30,40,40,50,60) Bag B has the following vouchers. BagB <- c(10,20,30,30,40,40,50,50, 50,50,50,50,60,60,60,60, 60,60,60,1000) Two values are selected (from BagA or BagB) without

Hi friends, Please can anyone help me with an easier solution of doing the below mentioned work. Suppose i have a dataset like this:--- i1 i2 i3 i4 i5 1 7 13 1 2 2 8 14 2 2 3 9 15 3 3 4 10 16 4 4 5 11 17 5 5 6 12 18 6 7 *i1,i2,i3,i4,i5 are my items.I am able to find all possible pairs i.e Say this dataframe is "item_pairs" **i1,i2 **i1,i3 **i1,i4 i1,i5 **i2,i1

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,

Hi, All, I have an n by m matrix with each entry between 1 and 15000. I want to know the frequency of each pair in 1:15000 that occur together in rows. So for example, if the matrix is 2 5 1 6 1 7 8 2 3 7 6 2 9 8 5 7 Pair (2,6) (un-ordered) occurs together in rows 1 and 3. I want to return the value 2 for this pair as well as that for all pairs. Is there a fast way to do this avoiding loops?

Hi Users, This is regarding the paired t-test. I have 5 variables (say) Data$v1,Data$v2,Data$v3,Data$v4,Data$v5 in my data frame. Now, I need to perform a paired t-test on all the possible 10 pairs.How do I set up the pairs table directly and pass those variables in to t-test. Thanks in advance, Pratap --------------------------------- Now you can chat without

Hallo, I have a table of names and values: joe 0.45 mike 0.34 jim 0.25 I would like to fill-in a table of all pairs of names (which I aleady have) joe.mike NA NA joe.jim NA NA mike.jim NA NA with the values from the first table in the order of the pairs. The outcome looks like joe.mike 0.45 0.34 joe.jim 0.45 0.25 mike.jim 0.34 0.25 Thanks a lot, Serguei [[alternative HTML version deleted]]

Hello all, Is there a way in R to compute the multivariate normal density of every pair of entries in a vector efficiently instead of using for loop? For example Suppose I have a vector a=c(v_1,...,v_p)=c(0.5343909, -0.7784353, -0.0568370, 1.8772838, -1.3183407, 0.8227418,...) I want to compute density(v_i, v_j) for every pair of entries (i,j) (i!=j) in a. The joint bivariate distribution

I have a list (length 750), each element containing a vector of unique strings (unique gene ids), with length up to ~40 (median 15). I want to compile a matrix of all possible triplets and their frequency within gene elements. Using combn and a lot of looping, I am accomplishing this but it is VERY slow. I've tried to figure out a way to vectorize this, using "match" and

This CAP will determine whether ARB_framebuffer_object can be enabled. The nv30 driver does not allow mixing swizzled and linear zsbuf/cbuf textures. Signed-off-by: Ilia Mirkin <imirkin at alum.mit.edu> --- src/gallium/docs/source/screen.rst | 3 +++ src/gallium/drivers/freedreno/freedreno_screen.c | 1 + src/gallium/drivers/i915/i915_screen.c | 1 +

For the series: Reviewed-by: Marek Ol??k <marek.olsak at amd.com> Marek On Sun, Oct 13, 2013 at 3:43 AM, Ilia Mirkin <imirkin at alum.mit.edu> wrote: > ping > > On Fri, Oct 4, 2013 at 4:32 AM, Ilia Mirkin <imirkin at alum.mit.edu> wrote: >> This CAP will determine whether ARB_framebuffer_object can be enabled. >> The nv30 driver does not allow mixing

Hi! is it allowed to create a constant and use it as operand for instructions in differend modules (but same context)? -Jochen

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

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 currently attempting to write a small program for a randomization test (based on rank/combination) for matched pairs. If you will please allow me to introduce you to some background information regarding the test prior to my question at hand, or you may skip down to the bold portion for my issue. There are two sample sizes; the data, as I am sure you guessed, is matched into pairs and

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

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 =

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 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 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