similar to: vectorized nested loop: apply a function that takes two rows

(Extremely sorry, disregard previous email as I hit send before pasting the latest version of the example; this one is smaller too) Dear R users, I want to apply a function that takes two vectors as input to all pairs (combinations (nrow(X), 2))of matrix rows in a matrix. I know that ideally, one should avoid loops in R, but after reading the docs for do.call, apply, etc, I still don't know

(Extremely sorry, disregard previous email as I hit send before pasting the latest version of the example; this one is smaller too) Dear R users, I want to apply a function that takes two vectors as input to all pairs (combinations (nrow(X), 2))of matrix rows in a matrix. I know that ideally, one should avoid loops in R, but after reading the docs for do.call, apply, etc, I still don't know

Dear R users, I need to normalize a bunch of row vectors. At a certain point I need to divide a matrix by a vector of norms. I find that the behavior of Matrix objects differs from normal matrix objects. Example the following code examples differ only in xnormed changing from normal to Matrix object: x = matrix(1:12,3,4) x = as(x, "CsparseMatrix") xnorms = sqrt(colSums(x^2))

Hi All, If you use vim to edit R code, you may be interested in this. I have put together a personalized syntax file, some code templates, and a way to send code from Vim to R using autoHotKeys (windows). http://www.andrew.cmu.edu/user/jquesada/RvimSuite/instructions.html Actually, the little autoHotKeys can be useful even if you don't use vim just to send the example R code from the help

Hi All, I recently found gmane http://gmane.org/ It's a system to covert mail to news and back, with the nice property of keeping a searchable archive... Very convenient if you are subscribed to many lists and don't want to have your mail box cluttered. I use it to read several mailing lists already, but R is not available there. I wonder if the admins know about gmane and if they

Hi, I got the following error. Sorry but this time I couldn't reproduce it with a simple chunk of code: .TM.repl.i.2col(): drop 'matrix' case ... Error in .nextMethod(x = x, i = i, j = j) : 'i' has no integer column number should never happen; please report In addition: Warning messages: 1: Ambiguous method selection for "%*%", target

Hi, I'd like to simply add column-wise using Matrix objects (Csparse). It looks like one can apply mosty any base function to these objects (i.e., apply, colSums), but there is a nasty conversion to traditional matrix objects if one does that. Is there any workaround? I can see colSum listed in the help for Class 'CsparseMatrix' , but I wonder whether I'm using the default

Hi, I'm finding that readMM() cannot read a file written with writeMM(). Example: library(Matrix) a = Matrix(c(1,0,3,0,0,5), 10, 10) a = as(a, "CsparseMatrix") writeMM(a, "kk.mm") b = readMM("kk.mm") Error in validObject(.Object) : invalid class "dgTMatrix" object: all row indices must be between 0 and nrow-1 Thoughts? Thanks, -Jose -- Jose

Dear all, I'm starting to learn R, but I'm already programing for a while, using ViM as editor. Therefore I'd like to be able to use R together with ViM. My question now is, whether there are already people out there knowing how to do this in a similar easy way as with Emacs, and if those would be willing to share this knowledge. I did already research on the web on this topic,

Hi, I need to multiply all columns in a matrix so something like apply(x,2,sum), but using multiplication should do. I have tried apply(x,2,"*") I know this must be trivial, but I get: Error in FUN(newX[, i], ...) : invalid unary operator The help for apply states that unary operators must be quoted. I tried single quotes too, with the same results. Thanks, -Jose -- Jose

Hello, I am wanting to use MRF to do multivariate regression. We are testing whether acoustic indices can predict structure (relative abundances) of vocalising avian community in UK and Ecuador. There are 26 acoustic indices, 65 UK species and 95 Ecuadorian species. I want to build a model for each ecozone (UK/ EC) using all species (relative abundance) as response matrix, and acoustic indices as

Hi, Has anyone run any R vs Python (numpy) tests? I'd love to see what the differences performance-wise are, specially handling large sparse matrices. Since both rely on external C code, there might not be much of a difference. If you know and use both languages, what are the main differences and what made you stick to one over another? I also noticed that there are strong libraries

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi, I'm doing some basic operations on large sparse matrices, for example getting a row. it takes close to 30 seconds on a 3Ghz machine, and shots the memory usage up to the sky. I suspect there are dense intermediary steps (which, if true would defeat the purpose of trying to use sparse representaitons). As much as I try understanding the

Dear R Users, I am getting a strange error, also relayed by Jose Quesada about a year ago. As below, in his message, I get "Error: bad value" to whatever I enter into the R console. My configuration is: - Windows XP SP2 - R 2.7.2 Has this problem been tracked down to a specific package ? I am using the following packages: library(strucchange) library(car) library(lmtest)

Hi, I'm attending summer School at UCLA (IPAM) on "probabilistics models of cognition". I have been an R-user since v. 1.4.1, but was trained in the frequentist tradition (as most psychologists!). I found that all faculty here use matlab and Murphy's bayes net toolbox. I have not had the need to use matlab before, and would love to stick to R for graphics models and

I have a pretty large sparse matrix of integers: > dim(tasa) [1] 91650 37651 I need to add one to it in order to take logs, but I'm getting the following error: > tasa = log(tasa + 1) CHOLMOD error: problem too large Error in asMethod(object) : Cholmod error `problem too large' I have 2 Gb of RAM, and the current workspace is barely 300mb. Is there any workaround to this?

I have a pretty large sparse matrix of integers: > dim(tasa) [1] 91650 37651 I need to add one to it in order to take logs, but I'm getting the following error: > tasa = log(tasa + 1) CHOLMOD error: problem too large Error in asMethod(object) : Cholmod error `problem too large' I have 2 Gb of RAM, and the current workspace is barely 300mb. Is there any workaround to this?

Hi, I'm finding a very strange error. For no good reason my R console (Rgui.exe, R 2.5.0, under win XP) stops producing anything meaningful, and just returns: Error: bad value to _whatever_ I enter. It starts doing this after a while, not immediately when launched. I have to restart R when this happens. No idea why. I didn't change anything in the R config that I remenber. Any

Dear all, below you find enclosed my message from January 9th and my program (attention: beginner). Thanks for both answers! a. However, as far as I know the cosine is not the same as the Pearson correlation (only in special cases). b. Reid Huntsinger's hint was very useful, however I had to transpose the matrix first, for I want to calculate the distance of the _rows_. Regards, Petra

Hi, I'm running this for a simulation study, so many combinations of parameter produce many predictions that I need to correlate with data. The problem ---------------- I'm using rating data with 3 to 5 categories (e.g., too low, correct, too high). The underlying continuous scales should be normal, so I chose the polychoric correlation. I'm using library(polychor) in its