similar to: Generalized Singular Value Decomposition (GSVD)

Hello, I would like to perform a generalized singular value decomposition with R. The only possibility I found is "GSVD" that is based on LAPACK/BLAS. Are there other possibilities too? If not, has anybody used LAPACK/BLAS under Windows XP? How can I install them? Following [1] did not help. I hope this is the right place for my question. Thank you very much! Oana Tomescu [1]

Hi All, I'm trying to run generalized singular value decomposition (GSVD) function from LAPACK library. Basically my problem is that I can not run it for large matrices, I get a memory error. I'm using R 2.5.1. I tried this on intel centos5 machines with 2 GB memory and 8 GB memory. I have unlimited max memory,cpu time and virtual memory. LAPACK is already compiled for R

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).

Dear R-users, I'd like to plot a three-dimensional surface and at the meantime I'm using an array. I would like to have the values of my first matrix in the heights of the plot and the colors of the single facet taking into account the second matrix. I hope that the next code will help all of you to understand better my issue, Thanks in advance, Giancarlo ############################ ##

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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

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Hi wizards, I have seen the function svd of R for singular value decomposition, but I need to computes the ``economy size'' or ``thin'' singular value decomposition of a matrix in R. Somebody knows how to do that?. Thanks in advance. -- Web Page http://geocities.com/lord_tyranus_96/

Hi, I need to computed the GSVD of two matrices. For doing so I used in my C code the lapack routine dggsvd. But when I source my file gsvd.R I have the following error: Error in eval.with.vis(expr, envir, enclos) : BLAS/LAPACK routine 'DGGSVD' gave error code -1 Is there a problem with the parameters passed through the gsvd.R script? Is there a problem within the C script?

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-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-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-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 <-

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

Hello, I'd like to draw a graphic using different color line segments to represent microarray data. It simply likes this: Data=cbind(c(1, 2, -1, 3, -2.2), c(1, 3, -1, -1.8, 4)) The first col No represents y'axis position (negative down and positive up). The second col No represents a length of segment (negative segment should be on left of y, and positive on right). Also the

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I am using R 2.2.1 on a Windows 2000 PC. When I do a grid() after the boxplot it overprints the boxplot: > boxplot(count ~ spray, data = InsectSprays, col = "lightgray") > grid(nx=NA, ny=NULL) > if I try the panel.first > boxplot(count ~ spray, data = InsectSprays, col = "lightgray", + panel.first=grid(nx=NA, ny=NULL)) > I can see the grid flash

Dear R-Users, without going into details I tried to prepare a simple example to show you where I would need help. In particular I prepare two examples-template for a study I'm conduction on discrete-time methods for survival analysis. Each of this example has two datasets which are basically equal, with the exception that in the former one has individual data and in the latter one aggregated

Dear R-list users, this question is not strictly related to R, but hopefully somebody will be able to answer. In a schematic way, which is the algorithm to sample from a multivariate normal distribution using the singular value decomposition? thank you for your help Stefano AVVISO IMPORTANTE: Questo messaggio di posta elettronica pu? contenere informazioni confidenziali, pertanto ? destinato