similar to: Confusing concept of vector and matrix in R

I know Matlab's M file can be converted to a stand-alone executable file. I wonder if there is a project aimed at compiling R scripts into stand-alone executable file. I think it will be very promising for R to be more widely used in different fields. -- View this message in context:

I used to consider using R and "Optim" to replace my commercial packages: Gauss and Matlab. But it turns out that "Optim" does not converge completely. The same data for Gauss and Matlab are converged very well. I see that there are too many packages based on "optim" and really doubt if they can be trusted! -- View this message in context:

Hi, (sorry for the wall of text; the issue here appears to be rather complicated) I'm seeing a somewhat strange case where checking whether an S4 object inherits from a parent class defined from another package with 'inherits' fails if that object is materialized through a call to 'load'. That's a mouthful, so I've put together a relatively small reproducible example

Hi, is there any way to keep a sub matrix dimension? exemple : i1<-1; i2<-1 j1<-2; j2<-3; ret <-matrix(1,4,4)[i1:i2,j1:j2] ; dim(ret) is NULL because the submatrix single col or single row is coerce to a vector automaticaly. How can i bypass this cast : submatrix->vector ??????? Thank you. --------------------------------- [[alternative HTML version

I should add one more item that may be related here -- calling 'methods:::.requirePackage' returns a different result based on whether the package namespace is already loaded or not. If the package namespace is not loaded, the package is loaded and attached, and the package environment is returned: > methods:::.requirePackage("digest") Loading required package:

I tried to use gpuCor function in the gputools package of R to calcuate the pairwise correlations of a matrix of 40,000 columns. Becuase there would be memory issues if I use the whole matrix at a time, I splitted the matrix into submatrix of 10,000 columns and then calculate the pairwise correlation of different submatrices. There are altogether 4 submatrices, so I need to calculate the pearson

Dear R-helpers I have the following problem: given a m x n matrix A, I want to have just a m x k submatrix B, with B[i,] = A[i, offset[i] + 1:k], e.g. from > offset <- c(0, 0, 1) > a <- matrix(1:9, 3) > a [,1] [,2] [,3] [1,] 1 4 7 [2,] 2 5 8 [3,] 3 6 9 the submatrix b 1 4 2 5 6 9 I can do this with a for loop or with sapply > b <-

Hi, I'm quite new to R, so excuse me if this problem has a simple solution. I'm working with an array, lets say i <- array(c(1:3,3:1), dim=c(3,2)) Then I want to give the rows and the columns names: rownames(i)<-c("a","b","c") colnames(i)<-c("d","e") The result is given below: d e a 1 3 b 2 2 c 3 1 Here comes my problem.

(Just returning from the "wilds" of Canada, so not able to comment on the specifics, but ...) There is a basic point about generic functions that may be related to the "private" class question and my earlier remarks that Martin alluded to. R (and S4 before it) allows packages to define methods for a generic function in another package. Say, for plot() in graphics. The

Does anyone have something like tapply that is extremely fast for matrices when there is a very large number of levels of the grouping variable? I'm referring to, for example, tapply(x, grouping.variable, function.operating.on.submatrix) where x is a matrix and the submatrix is a subset of the rows of x. The grouping variable's length equals the number of rows of x. -- Frank E

Hello everybody I'm very new at using R so probably this is a very stupid question. I have a matrix of "p" columns and I have to calculate for each of them the "two sample t-statistic" and p-value and to save the results into two different vectors. I have divided my matrix into two submatrices: submatrix A containing the first "n1" rows (p columns) and submatrix B

Hi, I have a simple question about matrix/data frame manipulation. I have a data frame that looks a something like this X Y Z 1 0 "apples" -1 -1 "oranges" ... 0 -1 "bananas" and I'd like to pull out all the rows for which X and Y are (un)equal into a submatrix. How can I do that? Many thanks, Roger Levy

Hi, I have a matrix that has a variable number of columns. I do not know, a priori, the number of columns. How can I get a sub matrix, for example, from row 10 to the end of the columns? In MatLab I would use something like this: SubMatrix = Matrix[10, 1:end] Thanks a lot. -- View this message in context: http://www.nabble.com/Get-data-from-matrix-tf4629336.html#a13218653 Sent from the R

Hi R-Wizards: I've looking through the R docs and have yet to find what I'm looking for and have tried a few intermediate steps to now avail yet and rather than spend another few hours looking for the solution, I figured I would post a message. I have a matrix (actually a set of them) that I want to pull all the names of the non-zero columns into a vector/list for further processing:

Hi, I have a matrix of say 1024x1024 and I want to look at it in chunks. That is I'd like to divide into a series of submatrices of order 2x2. | 1 2 3 4 5 6 7 8 ... | | 1 2 3 4 5 6 7 8 ... | | 1 2 3 4 5 6 7 8 ... | | 1 2 3 4 5 6 7 8 ... | ... So the first submatrix would be | 1 2 | | 1 2 | the second one would be | 3 4 | | 3 4 | and so on. That is I want the matrix to be evenly divided

Hello, I'm am in the process of trying to port a RATS functions to R and have the problem, that RATS allows for the creation of submatrixes that are linked to their basematrix. Basically it should work like this: a = matrix(1:(4*3),4,3) a # [,1] [,2] [,3] # [1,] 1 5 9 # [2,] 2 6 10 # [3,] 3 7 11 # [4,] 4 8 12 # This of course doesnt work :) b =

Dear listeRs, I'm finding that apply() behaves strangely when used on a 3-d array. For example: > at <- array(1:27,dim=c(3,3,3)) > at , , 1 [,1] [,2] [,3] [1,] 1 4 7 [2,] 2 5 8 [3,] 3 6 9 , , 2 [,1] [,2] [,3] [1,] 10 13 16 [2,] 11 14 17 [3,] 12 15 18 , , 3 [,1] [,2] [,3] [1,] 19 22 25 [2,] 20 23 26

Hello list, I try to optimize some R code and it turns out that the function as.matrix takes a lot of time in my code. There is only one reason why I need as.matrix: My code should work for matrices with ncol=p and p should be allowed to be 1 or larger. Now I have a matrix x with dim(x)=(n,p), and I need to work with the submatrix y <-x[gv,], (gv a vector of n logicals) and to calculate

Is there a good reason not to allow matrix extents to be zero? I have been writing a function which fits glms under certain linear constraints. I fit the model with a reduced set of variables and then transform back to the original set. This involves operating on submatrices of the covariance matrix and subsets of the coefficients. Sometimes these subsets are empty. A zero-length subset of the

I have a matrix M > dim(M) [1] 30380   561 I have another list L contains , that contains some row names of matrix M str (L)  chr [1:21037] Now I want to extract the submatrix subM (21037    ,    561)  from the matrix M by matching the rownames (M) to the 21037 rownames o f L How do I do that ? Thanks and regards, Pankaj Barah   Pankaj Barah Department of Biology  Norwegian University