similar to: Understanding dsyrk_ in C code

Following is a function that I wrote (It is working well). It's a simple one, nothing complicated. The only question that I have is a qutation mark issue, I guess. ############################################# funcname <- function(trait.file){ #line1 setwd('/root/subroot') # line 2 load('imge.RData')

Hi BioC user, I have a problem extracting the gene set I would like to work with. Here is I work with my data: normData <- read.delim("normalizedData.txt",sep ="\t") ######### two class unpaired comparison # y must take values 1,2 classes <- c(-1,-2,1,2) #prepere the data for the samr analysis data.x <-as.matrix(normData[,8:11]) d=list(x=data.x,y=classes,

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have the following data: > y [1] 0.000 0.004 0.008 0.016 0.024 0.032 0.044 0.064 0.072 0.088 0.108 0.140 [13] 0.156 0.180 0.208 0.236 0.264 0.296 0.320 0.360 0.408 0.444 0.472 0.524 [25] 0.576 > x [1] 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 [16] 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 I'd

Dear All: Significance Analysis of Microarrays(SAM) As we know sam do multiple t.test as following ## Default S3 method: t.test(x, y = NULL, alternative = c("two.sided", "less", "greater"),mu = 0, paired = FALSE, var.equal = FALSE,conf.level = 0.95, ...) var.equal: a logical variable indicating whether to treat the two variances as being equal. If 'TRUE'

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm generating a symmetric correlation matrix using a data matrix as input: mat <- cor(data.mat) My question is: Is there a more memory efficient way to store this data? For instance, since: all(mat == t(mat)) every value is duplicated, and I should be able to almost half the memory usage for large matrices. Any thoughts/comments? Cheers,

Dear R-help Hi, I'm Won. I try to do microarray normalization by R. I use justRMA function within affy package, got error about segment fault. I don't know why it happen. I attached error below. Please help me. Thank you. Cheers, Won ======================= OS : Redhat linux Cpu : intel xeon X5570 Memory : 26Gb & OS : Ubuntu Cpu : intel q6600 Memory : 8Gb

Having not much success with my previous question I try to reformulate it: I'm simulating a Markow chain in Fortran interfaced with R. Each loop of my Fortran calls various functions of the R RNG through the wrapper given below. In a run of 100 iterations of the Markov kernel, after 20 iterations, the RNG seems like frozen. For example, the first call to the RNG in my loop is:

I would like to call C routines from Fortran under linux as suggested in section 5.6 of the "Writing R extensions" documentation. I'm familiar with Fortran but not with C. I understand the example provided in Fortran: subroutine testit() double precision normrnd, x call rndstart() x = normrnd() call dblepr("X was", 5, x, 1) call rndend() end but I don't understand

Hi R usrs, I want to build R-2.10.0 on HP-UX, but I got following error message: ld: Unsatisfied symbol "zgemm" in file CHOLMOD.a[cholmod_l_super_numeric.o] ld: Unsatisfied symbol "zgemv" in file CHOLMOD.a[cholmod_l_super_solve.o] ld: Unsatisfied symbol "zherk" in file CHOLMOD.a[cholmod_l_super_numeric.o] ld: Unsatisfied symbol "ztrsm" in file

Hi, I have some trouble with the result of a fortran function calling the R binomial RNG: The C function rbinom is wrapped as in the file attached. My main fortran program starts as call rndstart() and ends as call rndend() I happen to call the binomial RNG within a loop as b = ggrbinom(1.d0,0.5d0) write(*,*) 'b=',b In certain cases, after a few iterations in the loop, b get

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I've written a function in R which takes a symmetrical matrix as input and processes all triplicate combinations of values from the matrix. The function looks something like: my_fun <- function(m) { if( nrow(mat) != ncol(mat) ) { stop("'m' must be a square matrix") } size <- nrow(m) for(x in 1:(size -2)) {

Are there any particular licences under which R packages must be released or is it the discretion of the author? The same question if the package is to be destined for CRAN? Kind regards, Nathan -- -------------------------------------------------------- Dr. Nathan S. Watson-Haigh OCE Post Doctoral Fellow CSIRO Livestock Industries Queensland Bioscience Precinct St Lucia, QLD 4067 Australia

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I was wondering if anyone could point me in the right direction for reading up on writing tests in R. I'm writing some functions for inclusion into a package and would like to test them to ensure they're doing what I expect them to do. Are these approaches used for testing packages in CRAN? Cheers, Nathan - -- -

Dear List, I am trying to modify the xlab and ylab for a current figure that was plotted by a package, I searched through the low level plotting command and they do not seem to contain how to do this (the only way is to use xlab, ylab as arguments in "plot" command, which I can not do since the plot is plotted using some other package, not by my own script). Is there any command for

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have a rectangular matrix of size 920 by 85. I'd like to coerce it into a square matrix such that all row/col names are present in the new matrix and the additional values are zero. As an example: A B C D A 1 2 3 4 E 5 6 7 8 F 9 10 11 12 Would be coerced to: A B C D E F A 1 2 3 4 5 9 B 2 0 0 0 6 10 C 3 0 0

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have some data generated as follows: <code> n <- 2000 work <- vector() for(x in 1:n) { work[x] <- sum(1:(n-x+1)) } plot(work) </code> What I want to do - ----------------- I want to split work into a number of unequal chunks such that the sum of the values in each chunk is approximately equal. The numbers in

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm trying to add some Fortran 90 code to an existing package. When I compile and load the file manually like: SHELL> R CMD SHLIB file.f90 R> dyn.load("file.so") I can use the .Fortran() fine. However, when I try to build, install and load the library I seem to be missing something. I do a: SHELL> R CMD build dir SHELL> R

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'd like to be able to colour histograms along the diagonal using the colours stored in colnames(d): > d black blue brown cyan 1 0.96405751 -0.02964390 -0.060147424 -0.06460070 2 -0.03614607 0.95475444 -0.152382053 -0.07767974 3 -0.07095613 -0.05884884 -0.061289399 -0.06445973 4 -0.03708223 -0.05997624

Dear list, I?m trying to register Fortran routines in randtoolbox (in srt/init.c file), see https://r-forge.r-project.org/scm/viewvc.php/pkg/randtoolbox/src/init.c?view=markup&root=rmetrics. Reading https://cran.r-project.org/doc/manuals/r-release/R-exts.html#Registering-native-routines and looking at what is done in stats package, I first thought that the following code will do the job:

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'm trying to calculate Pearson correlation coefficients for a large matrix of size 18563 x 18563. The following function takes about XX minutes to complete, and I'd like to do this calculation about 15 times and so speed is some what of an issue. Does anyone have any suggestions on ways to speed this up? I'd wondered if using C++ code to