similar to: Summing up diagonals w/o for-loop

Dear R-users, I would like to know whether there is a way to extract a diagonal of an inverse matrix without computing the inverse of the matrix itself. The size of my matrices are really huge and, also using sparse matrix, computing the inverse leads to storage problems and low speed. In other words, given a square matrix A, I aim to know diag(B), where B=solve(A), without computing solve(A).

? stato filtrato un testo allegato il cui set di caratteri non era indicato... Nome: non disponibile Url: https://stat.ethz.ch/pipermail/r-help/attachments/20060728/957eb23c/attachment.pl

Dear R-users, I would like to ask whether it's possible (for sure it would be), to plot each rows (or columns) in different graphs and in the same figure region without using the function "par" and then struggling around with "axes" and labels etc. Luckily, I would always have "rows + columns = even number" and the same "ylim". The next one could be a

Hi R-Help! I am trying to find a nicer way of extracting all the "complete" diagonals of a matrix. I am working with very large matrices that have many more rows than columns. I want to be able to extract each of the diagonals that are as long as the number of columns in the matrix. I have written a rather ugly function that presently does the job. It illustrates what I am trying to

Dear R-users, I'm struggling in R in order to "squeeze" a matrix without using a for-loop. Although my case is a bit more complex, the following example should help you to understand what I would like to do, but without the slow for-loop. Thanks in advance, Carlo Giovanni Camarda A <- matrix(1:54, ncol=6) # my original matrix A.new <- matrix(nrow=3, ncol=6) # a new

Hello, I am using Mac OS X on a power book and R 2.5.0 I try to extract a diagonal from a dissimilarity matrix made with dsvdis, with this code: diag(DiTestRR) But I get this error message: Fehler in array(0, c(n, p)) : 'dim' spezifiziert ein zu großes Array english: Error in array(0, c(n, p)) : 'dim' specifies a too big array. Is there a limit to extract diagonals? I

Dear R-users, I am searching to the "best" way to compute a series of n matrix multiplications between each matrix (mXm) in an array (mXmXn), and each column of a matrix (mXn). Please find below an example with four possible solutions. The first is a simple for-loop which one might avoid; the second solution employs the tensor product but then manually selects the right outcomes. The

Dear R-users, within the rgl-package, I would have a question about the usage of persp3d in combination of rgl.viewpoint. I am not able to figure out how to let a 3D plot rotating around likewise the example in ?rgl.viewpoint. It seems that when I use persp3d(...) I see something on my screen, which is different from what I get when it's rotating. Is there any different behavior between

Dear R-users, I would like to place two 3D plots side-by-side in a rgl-setting. It would nice to have something like "par(mfrow=c(1,2))" for basic plots, or an array framework for wireframe(lattice) (see example below). I only managed to overlap two persp3d plots. My final idea would be to animate both surfaces using play3d(rgl). Thanks in advance for any help. Best, Carlo Giovanni

Dear R-users, I am going to try to be as clearer as possible, showing also an example. 1) I have a function (in my real case it's much more complex) 2) I use "optim" to minimize 3) I want to use as method L-BFGS-B for several reasons 4) I know I could use "trace=6" (in "control") in order to see "live" the procedure 5) I would like to see separately the

Dear R-users, I am working with some grid-search optimization for 13 values of an object function. At glance one may compute the object function for each possible combination of set of parameters, but in my case would not be feasible: taking for example 13 possible values for each parameters like, in logarithm scale, 10^seq(-3,3,.5) will lead to 13^13 combinations of results. As a second trial

Dear R-users, I couldn't find a function or some help in R-project web about the Generalized Singular Value Decomposition. In MatLab there is a simple function for this algebric issue (gsvd). Is there anything like that in R? And, if not, could you help me to apply this method in R? Thanks in advance, Giancarlo +++++ This mail has been sent through the MPI for Demographic Rese...{{dropped}}

The following 1460 x 1460 matrix can be throught of as 16 distinct 365 x 365 matrices. I'm trying to set off-diaganol terms in the 16 sub-matrices with indices more than +/- 5 (days) from each other to zero using some for loops. This works well for some, but not all, of the for loops. The R code I"m using follows. For some reason the third loop below zero's-out everything in the

Hello, I'm attempting to access a specific number of sub diagonals in a MATRIX and have been accustomed to using spdiags in MATLAB or Octave. I've got a solution pieced together using for loops and it works though isn't vectorized and liable to run very slow for large matrices. As an example: A = 1 2 3 4 5 9 8 7 6 5 4 5 6 7 8 5 4 3 2 1 8 7 6 0 1 The subdiagonals are: 9,5,3,0 4,4,6

Dear R-friends, I use optim(par=c(mystartingpoints), fn=myloglikelihoodfunction, gr=NULL, method=c("L-BFGS-B"), ## I would like to do not use any bounds control=list(trace=6, ## just to see what it's going on maxit=c(20000)), ## to be sure the it doesn't stop reaching the max iterations

Dear R-user, I would like to apply spatial statistics on some historical data, in particular from 1850 to 1900 by registration district of England and Wales. I have searched in the R-archive, but unsuccessfully. Do you know whether R contains those shape files? Or where would be possible to download and use in R? Thanks in advance, Carlo Giovanni Camarda +++++ This mail has been sent through the

Dear R-users, would it be a better way to construct the matrix below without using any for-loop or model.matrix? preferably with some matrix algebra? Thanks in advance, Carlo Giovanni Camarda ## dimensions m <- 3 n <- 4 mn <- m*n k <- m+n-1 ## with a for-loop X <- matrix(0, mn, k) for(i in 1:n){ wr <- 1:m+(i-1)*m wc <- rev(1:m+(i-1)) where <- cbind(wr,wc)

? stato filtrato un testo allegato il cui set di caratteri non era indicato... Nome: non disponibile URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20100929/bedab79b/attachment.pl>

Dear R-users, I coded two equivalent ways to perform (in a simplified version) some matrix multiplications I would like to use in a more general framework. In the first case I used Kronecker product and vectorization of a certain matrix. This approach takes less time, but, as you may guess, I run out of memory when dimensions are large. In the second approach, I profited of sparseness and

Dear R-users, I would a small problem saving a graph with postscript after using xyplot. Whereas in the R-screen the two lines are solid, once the image is saved as .eps file the second lines (blue in the following example) is dotted. Here there is a simple example. Thanks in advance for your help, Carlo Giovanni Camarda # creating data a1 <- sort(runif(10)) a2 <- sort(runif(10)) a3 <-