similar to: ANNOUNCE--Rdsm package, a threads-like environment for R

I've just developed edtdbg, a small package that integrates R's debug() with one's text editor. Excerpt from the README file: Goal The debug() function in R is primitive. My goal was to make it more usable by integrating it with one's text editor. Hence I wrote the package here, edtdbg. Its features include: * As one steps from line to line of code

Dear All, 1. why did the problem happen? 2. How to solve it? -- Best wishes, Zhijiang Wang -------------------------------------------- PHD Student Room 212, Science buliding, The International WIC Institute, College of Computer Science and Technology, Beijing University of Technology, Beijing, China.

As I mentioned last week, I've been developing a package that I call Rdsm ("R distributed shared memory"), modeled after a similar package, PerlDSM, I wrote for Perl some years ago. It is now in alpha form, so I'm not uploading to CRAN yet, but it is definitely usable, and I am releasing it at http://heather.cs.ucdavis.edu/~matloff/R/Rdsm I hope many try it out, and give me

I am interested in running R commands asynchronously. My first choice is in the same R session that I am currently in. Here, the goal would be to run something like RunAsynchSameSession(myfunction(), "outputname.rda") Once RunAsynchSameSession had started myfunction(), RunAsynchSameSession would complete immediately. myfunction would keep going. It is OK if execution of the

On 2009-07-01, David M Smith <david at revolution-computing.com> wrote: > REvolution Computing has just released three new packages for R to > CRAN (under the open-source Apache 2.0 license): foreach, iterators, > and doMC. Together, they provide a simple, scalable parallel computing > framework for R that lets you take advantage of your multicore or > multiprocessor

Hi, I want to parallelize some computations when it's possible on multicore machines. Each computation produces a big objects that I don't want to store if not necessary: in the end only the object that best fits my data have to be returned. In non-parallel mode, a single gloabl object is updated if the current computation gets a better result than the best previously found. My plan

On 12.09.2018 20:20, G?bor Cs?rdi wrote: > This is all normal, a fork cluster works with processes, that do not > share memory. And if you are after shared-memory parallelism, you can try the 'Rdsm' package: https://cran.r-project.org/package=Rdsm Greetings Ralf -- Ralf Stubner Senior Software Engineer / Trainer daqana GmbH Dortustra?e 48 14467 Potsdam T: +49 331 23 61 93 11 F:

I am trying to add the bigmemory packages but I get the following error message: In file included from bigmemory.cpp:14:0: ../inst/include/bigmemory/isna.hpp: In function 'bool neginf(double)': ../inst/include/bigmemory/isna.hpp:22:57: error: 'isinf' was not declared in this scope make: *** [bigmemory.o] Error 1 ERROR: compilation failed for package 'bigmemory' * removing

Hello All, I tried to intall the bigmemory package from a CRAN mirror site and received the following output while installing. Any idea what's going on and how to fix it? The system details are provided below. --------------------- begin error messages ----------------------- * installing *source* package 'bigmemory' ... checking for Sun Studio compiler...no checking for

Hi all, Is there a way that I can import R functions into Fortran? Especially, I want to generate random numbers from some not-so-common distributions (e.g. inverted chi square) but did not find any routines written in Fortran that deal with distributions other than uniform and normal. Thanks. Anny [[alternative HTML version deleted]]

Hi, I am trying to run the bigmemory example provided on the http://www.bigmemory.org/ The example runs on the "airline data" and generates summary of the csv files:- library(bigmemory) library(biganalytics) x <- read.big.matrix("2005.csv", type="integer", header=TRUE, backingfile="airline.bin", descriptorfile="airline.desc",

Hi, I'm playing around with the 'bigmemory' package, and I have finally managed to create some really big matrices. However, only now I realize that there may not be functions made for what I want to do with the matrices... I would like to perform a cluster analysis based on a big.matrix. Googling around I have found indications that a certain kmeans.big.matrix() function should

Dear all, bigKRLS, which has been on CRAN for a couple of years, had to be pulled recently due to what seems to be a sanitizer issue stemming from its use of bigmemory. bigKRLS works fine (we?ve used it ourselves on many different platforms and have had over 15,000 downloads without an end user reporting difficulties because of this issue). Unfortunately, we have been unable to reproduce the

I work with problems that have rather large data requirements -- typically a bunch of multigig arrays. Given how generous R is with using memory, the only way for me to work with R has been to use bigmatrices from bigmemory package. One thing that is missing a bit is interoperability of bigmatrices with C++ and possibly java. What i mean by that is API that would allow read and write filebacked

Dear R-list I'm on my way to start a new project on a rather big panel, consisting of approximately 8 million observations in 30 waves of data and about 15 variables. I have a similar data set that is approximately 7 gigabytes in size. Until now I have done my data management in SAS, and Stata, mostly identifying spells, counting events in intervals, and a like, but I would like to

Hi there, I am using R on Windows here. And I got a rather stupid question: how can I create another R console? It would be nice to have multiple R consoles so that I can separate different types of commands I use. Thank you, Ivan [[alternative HTML version deleted]]

Hello, I have downloaded the rmutil package in the form of *.tar.gz compressed file (I would like to use the runge-kutta() function). The package rmutil does not appear in the list of available packages. Can any one help? Massoud Boroujerdi PhD [[alternative HTML version deleted]]

Hi everybody, well, I definitely don't understand anything. Why the hist function with freq=FALSE gives such a strange result??? R <- c(-1.10, 0.79, -1.17, -0.53, -0.26, -0.22, 0.29, -0.26, -0.26, 0.39) hist(R, freq=FALSE, breaks=10) Thanks everybody [[alternative HTML version deleted]]

Dear all, I am puzzled that how can i uninstall a R package that have been installed earlier (especially in MacOS). Any suggestion will be appreciated. -- Wenjun [[alternative HTML version deleted]]

To answer your first question about read.big.matrix(), we don't know what your acc3.dat file is, but it doesn't appear to have been detected as a standard file (like a CSV file) or -- perhaps -- doesn't even exist (or doesn't exist in your current directory)? Next: > In addition, I am planning to do a multiple imputation with MICE package > using the data read by bigmemory