similar to: Vector size limit for table() in R-2.15.1

Hi, I am trying to read in a rather large list of transactions using the arules library. It seems in the coerce method into the dgCmatrix, it somewhere calls unique. Unique.c throws an error when n > 536870912; however, when 4*n was modified to 2*n in 2004, the overflow protection should have changed from 2^29 to 2^30, right? If so, how would I change it in my copy? Do I have to recompile

The MKsetup() in unique.c throws an error if the vector to be hashed is longer than (2^32)/8: if(n < 0 || n > 536870912) /* protect against overflow to -ve */ error(_("length %d is too large for hashing"), n); I occasionally work with vectors longer than this on 64-bit builds. Would it be too much to ask that R can take advantage of all 64 bits for hashing when

Looking at shash in unique.c, from R-2.10.1 I'm wondering if it makes sense to hash the pointer itself rather than the string it points to? In other words could the SEXP pointer be cast to unsigned int and the usual scatter be called on that as if it were integer? shash would look like a slightly modified version of ihash like this : static int shash(SEXP x, int indx, HashData *d) {

Dear all, my question might be a bit off-topic. Is there anything like a standard textbook on statistical programming? With that I don't mean anything like MASS, S Programming, Programming with Data, ... (no offense meant, they are fantastic books and each of those three helped me a great deal). Rather in the direction of the "Numerical Recipes" Series addressing how to implement

Full_Name: Vilmos Prokaj Version: R 2.7.1 OS: windows Submission from: (NULL) (213.181.195.84) Dear developers, The following line of code (produced by a mistake) caused an infinite loop unique("a",c("a","b")) or also unique(1,1:2) I made a little investigation, and it seems to be that the following function from unique.c is looping infinitely static int

sort() and order() are not quite the same, as "one knows": o order allows breaking ties by more than one argument; o sort allows a 'partial' and 'na.last' argument Still, the following timing (on a `simple' UltraSparc I) suggest that actually two different algorithms are used > N <- 10000 > typeof(x0 <- 1:N) # --- x0 : already sorted --- [1]

Hi All, I have a Quantum scalar i40 tape library. I need to configure it to TWO tape partition libraries, e.g., library_a and library_b, so that each library has its own tape drive. Then connect this physical tape library to two different CentOS servers so that each server can see its own media changer and tape drive. I once had a successful configuration on one host but NOT on the other. One

Hello R-users, I have a symmetric matrix of numerical values and I want to obtain those values in the upper or lower triangle of the matrix in a vector. I tried to do the job by using two for-loops but it doens't seem to be a clever way, and I'd like to know a more efficient code for a large matrix of thousands of rows and columns. Below is my code for your reference. Thanks a lot.

Hi Suppose I have a matrix (cohort are rows and years are columns) [2000] [2001] [2002] [2003] [C1] 0.01 0.03 0.02 0.09 [C2] 0.06 0.05 0.07 0.11 [C3] 0.1 0.5 0.4 0.98 [C4] 0.7 0.6 0.2 0.77 I want to extracts the diagonals to get a matrix which looks like this (C1 becomes C2 in 2002, C2 becomes C3 in 2003

Dear R Folks, I'm a big fan of R, but there are a couple of things that repeatedly annoy me, and I wondered if anyone has neat ways to deal with them. (a) When using "apply" row-wise to a matrix, it returns the results column-wise, and to preserve the original orientation, I've to do a transpose. E.g. I've to keep doing a transpose, which I consider to be quite

Hi, I'm still not quite there with my H-F (G-G) correction code. I have it working for the main effects, but I just can't figure out how to do it for the effect interactions. The thing I really don't know (and can't find anything about) is how to calculate the covariance matrix for the interaction between the two (or even n) main factors. I've looked through some books

Hi, I'm still not quite there with my H-F (G-G) correction code. I have it working for the main effects, but I just can't figure out how to do it for the effect interactions. The thing I really don't know (and can't find anything about) is how to calculate the covariance matrix for the interaction between the two (or even n) main factors. I've looked through some books

My unit's firmware: library 05.03, tape d22h, shows the device as set to random mode. But mtx -f /dev/st0 status gives an error that google says the device is in sequential mode. dmesg|grep -i hp does reflect CentOS thinks the device is a sequential unit. I've tried this with Fedora 8, too, and both show the same, so it is either an issue with CentOS/Fedora RPMs, or the version of

Hello all, To calculate the power of a matrix, I used the command "mtx.exp(X, n)", but there is an error saying "Error: couldn't find function "mtx.exp"". How can I deal with this problem? Jing

I have the following xyplot figure: http://img577.imageshack.us/img577/686/filesizeresults12000000.png The data are organized in a matrix file as follows: Type Elements Chromosome Time bedGz 12000000 chr1 14.240 bedGz 12000000 chr2 7.949 bedGz 12000000 chr3 5.103 bedGz 12000000 chr4 5.290 bedGz 12000000 chr5 5.161 ... The x-axis labels in the Chromosome column are ordered

Hello, I'm new on this list. First of all, thank you to all the developers of this great project! At the moment there is only an application that keeps me on both macos and windows, its name is PWGL a free environment for computer assisted composition in openGL. (http://www2.siba.fi/PWGL/) I'm running Ubuntu 8.04 and wine 0.9.59. I have to say that I also installed vcrun2005 and

Dear all, I have a population with three age-classes, at time t=0 the population is: n.zero <- c(1,0,0) I have a transition matrix A which denotes "fertility" and "survival": A <- matrix(c(0,1,5, 0.3,0,0, 0,0.5,0), ncol=3, byrow=TRUE) To obtain the population at t=1, I calculate: A %*% n.zero To obtain the population t=2, I calculate: A %*% (A %*% n.zero) ... and so

Dear R colleagues, as a result of my calculations regarding the inter-observer-variability in bronchoscopy, I get a confusion matrix like the following: 0 1 1001 1010 11 0 609 11 54 36 6 1 1 2 6 0 2 10 14 0 0 8 4 100 4 0 0 0 0 1000 23 7 12 10 5 1001 0 0 4 0 0 1010 4 0 0 3 0 1011 1 0 1 0 2 11

I have an array with names which contain multibyte characters. ?When I try to write the array to a file using write.table and row.names = T I receive an error message when the first such name is encountered, saying that I have not specified the option to generate NA instead. ?I really would be satisfied if the row name in the file were exactly what is displayed when I print the array on the

Dear all, I would like to compute power of a square non symmetric matrix. This is a part of a simulation study. Matrices are quite large (e.g., 900 by 900), and contains many 0 (more than 99 %). I have try the function mtx.exp of the Biodem package: library(Biodem) m <- matrix(0, 900, 900) i <- sample(1:900, 3000, replace = T) j <- sample(1:900, 3000, replace = T) for(x in 1:3000)