similar to: matrix problem

Hi, In the example you showed: m1<- matrix(0,length(vec),max(vec)) 1*!upper.tri(m1) #or ?m1[!upper.tri(m1)] <-? rep(rep(1,length(vec)),vec) #But, in a case like below, perhaps: vec1<- c(3,4,5) ?m2<- matrix(0,length(vec1),max(vec1)) ?indx <- cbind(rep(seq_along(vec1),vec1),unlist(tapply(vec1,list(vec1),FUN=seq),use.names=FALSE)) m2[indx]<- 1 ?m2 #???? [,1] [,2] [,3] [,4] [,5]

> Hello, > > Is this the fastest way to use indices from one matrix to reference rows > in another smaller matrix? I am dealing with very big data (lots of columns > and I have to do this lots of times). > > ######sample data ############## > vals = matrix(LETTERS[1:9], nrow=3,ncol=3) > colnames(vals) = c('col1','col2','col3') > rownames(vals)

I would like to be able to randomise presence-absence (i.e. binary) matrices whilst keeping both the row and column totals constant. Is there a function in R that would allow me to do this? I'm working with vegetation presence-absence matrices based on field observations. The matrices are formatted to have sites as rows and species as columns. The presence of a species on a site is

Hello, All, I have a dataset that looks like this: x <- matrix(c( 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 2, 1, 1, 2, 1, 1, 3, 1, 1, 3, 1, 1, 3, 1), ncol = 5, byrow = T, dimnames = list(1:10, c("gender", "race", "disease"))) I want to write a function to produce several matrices including only ?TRUE? and ?FALSE? for the different levels of the

Dear R users, I want to check matrices when i change the order of the rows or/and the order of the columns or/and the combination of them i will give an example what i want  1  -1  1  1      1  1   1  1 -1  -1 -1 -1    -1 -1  -1  -1   1  1    1  1     1 -1    1   1 these 2 matrices are identical because i change the first row and make it third   1  -1  1  1      -1  1   1  1 -1  -1 -1

I'd like to remove duplicated rows within a matrix, with missing data being treated as wildcards. For example > x <- matrix((1:3), 5, 3) > x[4,2] = NA > x[3,3] = NA > x [,1] [,2] [,3] [1,] 1 3 2 [2,] 2 1 3 [3,] 3 2 NA [4,] 1 NA 2 [5,] 2 1 3 I would like to obtain [,1] [,2] [,3] [1,] 1 3 2 [2,] 2 1 3

Dear List: I am having to build a block-diagonal matrix (vl) and am currently using the following code. I<-diag(sample.size) vl<-kronecker(I,vl.mat) This code works fine, but for large N, it is a huge memory hog. Is there a more efficient method for constructing vl? Thanks, Harold [[alternative HTML version deleted]]

Dear all, According to CHANGES IN R 3.0.0: o diag() as used to generate a diagonal matrix has been re-written in C for speed and less memory usage. It now forces the result to be numeric in the case diag(x) since it is said to have 'zero off-diagonal entries'. diag(x) does not work for character vector in R 3.0.0 any more. For example, v <- c("a",

Dear R experts, I have 2 matix: A& B. I am trying to index B against A - (1) find out B rows that fall between the col 1 and 2 of A& put them into a new vector SNP.I made code as below, but I cannot think of a right way to do it. Could anyone help me with the code? Thanks,Jiang---- A <-

Dear R users, Suppose i have an A square matrix rxr. I want to obtain a block matrix B (pxr,pxr) where the p diagonal blocks are A and the others values are 0. I would like to do something like : diag(A,ncol=pr, nrow=pr) How can i do it ?? Thanks in advance, Olivier. -- -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- Olivier MARTIN PhD student phone: (33) 04

I have a matrix of frequency counts from 0-160. x<-as.matrix(c(0,1,0,0,1,0,0,0,1,0,0,0,0,1)) I would like to apply a function creating a new column (x[,2])containing values equal to: a) log(x[m,1]) if x[m,1] > 0; and b) for all x[m,1]= 0, log(next x[m,1] > 0 / count of preceding zero values +1) for example, x[1,2] should equal log(x[2,1]/2) = log(1/2) = -0.6931472 whereas x[3,2] should

Could someone please suggest a more clever solution to the following problem than my loop below? Given X a 2xN matrix X, and I a k-subset of N, Generate the (2^k)xN matrix Y with columns not in I all zero and the other columns with all choices of an entry from the first or second row of X. For example, with X <- matrix(1:8, nrow=2) I <- c(1,3) X is 1 3 5 7 2 4 6 8 and Y should be 1 0 5

Dear List, I am writing a custom panel function and xyplot method to plot the results of a procrustes analysis from the vegan package. I am having trouble getting the call to panel.arrows to work as I wish when conditioning. The attached file contains the function definitions for the xyplot method and the custom panel and prepanel functions I am using. This example, using data and functions from

Dear R users, I have a question about matrix manipulation with its rows. Plz see the simple example below sample <- list(matrix(1:6, nr=2,nc=3), matrix(7:12, nr=2,nc=3), matrix(13:18,nr=2,nc=3)) > sample [[1]] [,1] [,2] [,3] [1,] 1 3 5 [2,] 2 4 6 [[2]] [,1] [,2] [,3] [1,] 7 9 11 [2,] 8 10 12 [[3]] [,1] [,2] [,3] [1,] 13 15 17 [2,]

I've been doing some consulting with students who seem to come to R from SAS. They are usually pre-occupied with do loops and it is tough to persuade them to trust R lists rather than keeping 100s of named matrices floating around. Often it happens that there is a list with lots of matrices or data frames in it and we need to "stack those together". I thought it would be a simple

In do_matrix in src/array.c there is a type switch containing : case LGLSXP : for (i = 0; i < nr; i++) for (j = 0; j < nc; j++) LOGICAL(ans)[i + j * NR] = NA_LOGICAL; That seems page inefficient, iiuc. Think it should be : case LGLSXP : for (j = 0; j < nc; j++) for (i = 0; i < nr; i++) LOGICAL(ans)[i + j * NR] = NA_LOGICAL; or more simply : case

Hi, I would like to replace all the max values per row with "1" and all other values with "0". If there are two max values, then "0" for both. Example: from: 2 3 0 0 200 30 0 0 2 50 0 0 3 0 0 0 0 8 8 0 to: 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 Thanks! -- View this message in context:

Dear R-Helpers, I have a matrix where the first column is known. The second column is the result of multiplying this first column with a constant "const". The third column is the result of multiplying the second column with "const"..... So far, I did it like this (as a simplified example): nr.of.columns <- 4 myconstant <- 27.5 mymatrix <- matrix(numeric(0), nrow=5,

Dear List, I have a problem I'm finding it difficult to make headway with. Say I have 6 ordered observations, and I want to find all combinations of splitting these 6 ordered observations in g groups, where g = 1, ..., 6. Groups can only be formed by adjacent observations, so observations 1 and 4 can't be in a group on their own, only if 1,2,3&4 are all in the group. For example,

Dear R-users, Does anybody know how to construct a block-diagonal matrix (with the blocks being different matrixs, concerning the dimension and the values) ? I would like to know also if there is any package that generates values from a multivariate skew normal distribution. Thanks all, Caio --------------------------------- [[alternative HTML version deleted]]