similar to: Why was my R process killed spontaneously?

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 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 all, I'm working with a large data set (on the order of 300X300) and trying to apply a function which compares the elements of all possible 2x2 submatrices. There are rc(r-1)(c-1) such submatrices, so obviously the naive method of looping through the rows and columns is computationally unfeasible for my data set: for(i in 1:(nrow(data)-1)) { for(j in (i+1):nrow(data)) { for (m

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

Dear R-help list, Pls I have this problem. Suppose I have a matrix of size nxn say, generated as follows   z<-matrix(rnorm(n*n,0,1),nrow=n)   I want to write a function such that for i in 1:n, I will remove the rows and columns corresponding to i (so, will be left with n-1*n-1 submatrix in each cases). Now I need the sum of the determinant of each of this submatrices. As an example, if n=3, it

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

Hi all, I have a R script that creates several input files for an analysis program. It loops through the matrix read into R and picks out submatrices and then creates a separate output file for each submatrix. The loop works great, but I am having trouble getting all the separate output files written. The line I have is: write.table(ch1d,

Yes you are right ... an example is mandatory. So ... I have a matrix of 0 with just a single 1 per row and per column I need to extract all maximal 'diagonal' submatrices Let's say I have the following matrix A B C D E a 0 1 0 0 0 b 1 0 0 0 0 c 0 0 1 0 0 d 0 0 0 1 0 e 0 0 0 0 1 well I would like to get, for this example, the two following submatrices A B C D E

Dear Rxperts Below is a small vector of values of zeros and non-zeros... was wondering if there is an efficient way to get the block sizes of submatrices of a big matrix similar to the one shown below? diagonal elements can be zero too. Rows with only a diagonal element may be considered as a unit block size. c(1,0,0,0,0,0,0,0,0,0,0, 1,1,0,0,0,0,0,0,0,0,0, 0,0,1,0,0,0,0,0,0,0,0,

Hi there and thanks in advance. I have a large symmetrical matrix stored in a text file. After load in R I would like to extract the same number of columns and rows (symmetrical submatrix) using their labels. I have tried this code in order to extract columns, but R console gives me the "+" sign at the end of the code, pointing out incomplete command, so it is not working:

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 everybody, I'm looking for an optimal way to split a big matrix (e.g. ncol = 8, nrow=8) into small square submatrices (e.g. ncol=2, nrow=2) For example If I have > h [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 1 9 17 25 33 41 49 57 [2,] 2 10 18 26 34 42 50 58 [3,] 3 11 19 27 35 43 51 59 [4,] 4 12 20 28 36

Dear all, I have a large matrix with about 2500 variables, and 100 rows. I would like to calculate the means of the every 10 variables starting from 1:2500 and saving the results as a vector or matrix. How can I do that? Alternatively, How can I create 250 subset matrices in the order of variables 1:2500 in groups of 10 from the single matrix which had initially 2500 variables ? I guess I have

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:

El código que me olvide pegar input m <- structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 4, 4, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 5, 5, 5), .Dim = c(10L, 5L)) m ## output output <- c(1:3, 1:5, 1:2) output nfilas <- nrow(m) while(nfilas > 0) { diagonal <- diag(m)

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 <-

Why does R need the concept of "Vector"? In my opinion, it is a useless and confusing concept. A vector is simply a special case of a matrix whose row or column number is equal to 1. When I take submatrix from one matrix and if row or column number is 1, R will automatically convert it into a vector. It is very straightforward that a submatrix of a matrix should be a matrix. In

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.