similar to: Speeding up resampling of rows from a large matrix

Dear R users, Two questions: 1) Is there a way to simplify the mtext() line below ? beta=c(1,-1) m=5 plot(1) mtext( bquote(paste( beta == .(paste( "(", paste(beta, collapse=", "), ")" )) )), outer=TRUE,line=-3) 2) How do I get the embedded carriage return "\n" below to work, i.e for the text that follows it to appear on the next line? beta=c(1,-1) m=5

Dear R users, Consider the following example function: f = function(a,b) { g = function(x) a*x + b h = function(x) g(x)^2 + x^2 opt = optimize(h,lower = -1, upper = 1) x.min = opt$minimum h.xmin = opt$objective g.xmin = g(x.min) return(c(x.min, h.xmin, g.xmin)) } In my real problem the function that plays the role of "g" is costly to compute. Now, to

I've looked through all of the posts about this issue (and there are plenty!) but I am still unable to solve the error. ERROR: cannot allocate vector of size 455 Mb I am using R 2.6.2 - x86_64 on a Linux x86_64 Redhat cluster system. When I log in, based on the specs I provide [qsub -I -X -l arch=x86_64] I am randomly assigned to a x86_64 node. I am using package GenABEL. My data (~ 650,000

Hi everyone, I'm using the function 'HWE.exact' of 'genetics' package to compute p-values of the HWE test. My data set consists of ~600 subjects (cases and controls) typed at ~ 10K SNP markers; the test is applied separately to cases and controls. The genotypes are stored in a list of 'genotype' objects, all.geno, and p-values are calculated inside the loop over all

I've searched the archives and read the xyplot help but can't figure out the 2 lattice questions below? Consider: library(lattice) DF <- data.frame(x=rnorm(20), y=rnorm(20), g1=rep(letters[1:2], 10), g2=rep(LETTERS[1:2], each=10), g3=rep(rep(letters[3:4],each=5),2)) xyplot(y ~ x | g1 + g2, groups=g3, data=DF) 1) Is there a way to get one strip per row and column

Hi Mr Tierney, I have noticed an error message from R 1.12.x's CMD check for a while (apparently prof Ripley completely rewrote CMD check in R 1.12+) e.g.: http://bioconductor.org/checkResults/2.7/bioc-LATEST/snpMatrix/lamb2-checksrc.html ---------------- * checking R code for possible problems ... NOTE Warning: non-unique value when setting 'row.names': ?new? Error in

Dear R developers: I am a PHD candidate student in the school of public health of Peking University and my major is genetic epidemiology. I am learning the FAM-MDR algorithm, which is used to detect the gene-gene and gene-environment interactions in the data of pedigree. The codes were written by Tom Cattaert of the University of Liege. The algorithms and the sample datasets are available at

Dear R-helpers, I need to insert an R (2.6.0) generated plot containing semi-transparent colors into PowerPoint (2002). When I directly paste it from the clipboard or insert it as (enhanced) Metafile (I'm on Windows XP) the semi-transparent colors don't show. When I insert it at as a Bmp, Png or Jpeg and then convert to PDF the semitransparent colors do show but the quality of the image

Dear R list, I've read the function writing sections on both "An introduction to R" and "R language Definition" manuals but still don't understand why the following gives an error message: fun <- function(x, ...) x + y fun(1, y=2) I get: Error in fun(1, y = 2) : object "y" not found I'd appreciate any help in understanding this. R version 2.4.1

Dear R helpers, I have a data frame where missing values for numeric variables are coded as 999. I want to recode those as NAs. The following only partially succeeds because numeric variables are converted to character in the process: df <- data.frame(a=c(999,1,999,2), b=LETTERS[1:4]) is.na(df[2,1]) <- TRUE df a b 1 999 A 2 NA B 3 999 C 4 2 D is.numeric(df$a) [1] TRUE

I am using dgc.genetics to perform TDT analysis on SNP data from a cohort of trios. I now have a file with about 6008 variables. The first few variables related to the pedigree data such as the pedigree ID the person ID etc. Thereafter each variable is a specific locus or marker. The variables are named by a pattern such as "Genotype.nnnnn" with nnnnn corresponding to a number which

Hallo, I didn´t found any facilities for Halbergs cosinor analysis in R. This analysis is well known in the Chronobiology as the least square approximation of time series using cosine function of known period (in my case of 24hours-period). I tried to write a script but crashed... Can you give me some advices, please!? Thanks Anne Berger Institute of Zoo- and Wildlife Research, Berlin, Germany

Hi All, is there any chance of vectorising the two ifelse() statements in the following code: for(i in gp){ new[i,1] = ifelse(srow[i]>0, new[srow[i],zippo[i]], sample(1:100, 1, prob =Y1, rep = T)) new[i,2] = ifelse(drow[i]>0, new[drow[i]>0,zappo[i]], sample(1:100, 1, prob =Y1, rep = T)) } Where I am forced to check if the value of drow and srow are >0 for each line... in

Dear R mailing list, I have a dataset with genotypes from trios and I would like to infer haplotypes for each mother, father and child. The package that I could find that can do this is tdthap. But when the mother is homozygous (e.g., 2/2) the haplotype is called as not possible to infer (0); I would prefer for it to call the genotype (2). From what I understand it is doing what I would like

Hi all, I've been looking in R for an EM algorithm adjusted for multiple-locus haplotypes frequencies, but failed in 100%. Has anyone heard of anything of this kind in R? Thanks in advance, Marcin

Dear all, As our previous email did not get any response, we try again with a reformulated question! We are trying to do something which needs an efficient loop over a huge array, possibly functions such as apply and related (tapply, lapply...?), but can't really understand syntax and examples in practice...i.e. cant' make it work. to be more specific: we are trying to apply a mask

Dear R developers, I was looking for a function analogous to base::diag() for getting and setting bands of a matrix. The closest I could find was Matrix::band(), but this was not exactly what I wanted for two reasons. Firstly, Matrix::band() returns a matrix rather than just the specified band. Secondly, Matrix::band() cannot be used for setting the values for a matrix band. Setting or

Dear all I would like to ask you if an assignment can be done inside a lapply statement. For example I would like to covert a double nested for loop for (i in c(1:dimx)){ for (j in c(1:dimy)){ Powermap[i,j] <- Pr(c(i,j),c(PRX,PRY),f) } } to something like that: ij<-expand.grid(i=seq(1:dimx),j=(1:dimy)) unlist(lapply(1:nrow(ij),function(rowId) { return

I am out of my league with this question. The following code starts the java imaging program ImageJ from within R, and displays an image (assuming ImageJ is installed on your computer). library(RImageJ) img <- IJ$openImage( file.choose() ) #pick an available .tif file img$show() # make the image object visible # An image is now displayed # find out about the objects involved >

I need to refresh my memory on Probability Theory, especially on conditional probability. In particular, I want to solve the following two problems. Can somebody point me some good books on Probability Theory? Thank you! 1. Z=X+Y, where X and Y are independent random variables and their distributions are known. Now, I want to compute E(X | Z = z). 2.Suppose that I have $I \times J$ random number