similar to: [R] R functionality

I am considering getting the rpvm package for running a parallel virtual machine working on Splus. That package contains a considerable amount of C-level code written to interface R with the pvm3 library functions and of course all of it uses the R macros and conventions associated with the R-style ".Call". It looks as though it might be possible to automatically transform that code to

Would it be hard to make the X11 device driver in R accept general X11 resources? In particular I would like to be able to set the title of the graphics window when I start it up. (Note this is not the same thing as the title of a plot but rather is the character string visible to the window manager, and usually goes in a titlebar on top.) For example in Splus one can do > motif('-xrm

The initial authors of R said?, "...we implemented the language by first writing an interpreter for a Scheme subset and then progressively mutating it to resemble S." Further on in that article they elaborated that their strategy was to create a parser that would take expressions in S-like syntax and translate them to Scheme S-expressions. Does R still work that way? Can R be made to

Is there anything R can do that Splus can't? I know about the differences in the language but what about statistical functionality. Are there models you can build or graphs you can plot in R that you can't in Splus? My impression is that in this respect R is strictly a subset. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hello- Since my data bank in SPSS has > 40 variables, I think that R crashes because of the memory limit. In Maindonald?s UsingR text, on pg 3, there?s a footnote that reads: "If you want larger memory space than the default you may want a target akin to <path to binary>\rw091\bin\rgui.exe --visize 30M --nsize 1000K [The default is --vsize 6M --nsize 250K

At 14:35 02/10/00 +0800, mohd zamri wrote: >new to R and starting to learn to program R. The underscore ("_") did some >suprising result. e.g > >> c <- c(1,2,3,4,5) >> mean(c) >[1] 3 >> c_mean <- mean(c) >> c >[1] 3 > >having some experience in C, I thought the underscore is "always" valid in >variable name. totally confuse

Dear R-users, After the reading of "Writing R extensions", "readme.packages", "Using external compilers with R", ..., I have tried to create a DLL for my Fortran file using the command: g77 --shared -o robeth.dll robeth.f and failed with several messages as : c:\temp/ccU8N5fb.o: ... undefined reference to 'realpr_' c:\temp/ccU8N5fb.o: ... undefined

Hello, I'm trying to source() an SPlus 6.x file created using dump(..., oldStyle=T) into R (version 2.01) as using the following instructions: > *If you have access to S-PLUS, it is usually more reliable to |dump| > the object(s) in S-PLUS and |source| the dumpfile in R. For S-PLUS 5.x > and 6.x you may need to use |dump(..., oldStyle=T)|, and to read in > very large objects

I wanted a function that would give the euclidean distance of a vector. Then I was happy, because I found vecnorm listed on pg 55 of V&R (3rd edn) which I had just bought today. Then I was sad, because R did not have vecnorm. Then I was happy again, because I bethought myself that I could copy the function vecnorm from splus to my code. Then I was sad again because R complained >

I am trying to translate code from S-PLUS to R and R really struggles! After starting R with the foll. R --vsize 50M --nsize 6M --no-restore on a 400 MHz Pentium with 192 MB of memory running Linux (RH 6.2), I run a function that essentially picks up an external dataset with 2121 rows and 30 columns and builds a lm() object and also runs step() ... the step() takes forever to run...(takes very

I have been using SPLUS on UNIX to do performance analysis of our computers and have some matrices that are about 15M rows with 8 columns. These are 'integers' and therefore take up about 500M of memory. I run on a system with 2G of memory and will utilize over a 1G when processing this data. I am considering using R and was wondering how large addresses spaces are handled under

Hi, I have a few questions about how to handle large data sets in R. What is the size of the largest matrix that R can comfortably deal with? Is this size limit imposed by R's software, or is it a question of the machine that one runs on? How does one go about choosing reasonable values of vsize and nsize? I have a data set with about 1,000,000 rows, and 30

Hi , I ''ve got a trouble with using R. When I want to load a file that contains 93 thousand raws and 22 colums of data (essentially float) R shows me this error message "heap size trouble" Does anyone could tell me what parameter shall I precise before launching R in order to load my big file. Thanks a lot -------------- next part -------------- A non-text attachment was

Dear R users, I have noticed that my R startup is extremely slow. It takes almost 3 minutes from "double-click" to R prompt. I have been running R-0.64.1 till recently and it took about 30 sec. I still have access to R-0.64.1. When I started it up, it took about 25 sec. Can anyone tell me if this is a bug in R or a problem with my machine? Note: This is after bootup with R being the

Dear R-ers, somehow it is not possible to increase nsize to more than 20000k. When I specify e.g. > R --vsize=10M --nsize=21000K the result is: free total (Mb) Ncells 99658 350000 6.7 Vcells 1219173 1310720 10.0 Maybe I have overlooked s.th.... Marcus -- +------------------------------------------------------- | Marcus Eger | E-Mail: eger.m at gmx.de (NEW) |

We have a project that calls for the creation of a list of many distribution objects. Distributions can be of various types, with various parameters, but we ran into some problems. I started testing on a simple list of rnorm-based objects. I was a little surprised at the RAM storage requirements, here's an example: N <- 10000 closureList <- vector("list", N) nsize = sample(x

>>>>> "PG" == Philippe Grosjean <phgrosje at ulb.ac.be> writes: PG> I am interested by your list of students wishes, since I am PG> developing a GPL user interface for math/stat calculation PG> engines (among others: R and Splus, but also Octave, Scilab PG> and Mathematica,...). It will run under Windows only (for the PG> moment),

I am trying to use tree to partition a data set. The data set has 3924 observations. Partitioning seems to work for small subsets of the data, but when I use the entire data set, no partitioning occurs. The variables are: RESP respondent to a survey (0 = not a respondent, 1 = respondent) AGE_P Age (continuous) ORIGIN_I Hispanic Ethnicity (1 = Hispanic, 2 = non-Hispanic) RACRECI2 Race

I am running R version ??? under Redhat 5.2. It seems as though the --nsize object has no effct on the size of the allocated Ncells as determined using gc(). Yes, I have that much data.... That is if I envoke R with R --vsize 100 --nsize 5000000 then type gc() I get free total Ncells 92202 200000 Vcells 12928414 13107200 Thanks Tony Long Ecology and Evolutionary Biology Steinhaus

hi all i know that one should try and limit the amount of looping in R programs. i have supplied some code below. i am interested in seeing how the code cold be rewritten if we dont use the loops. a brief overview of what is done in the code. ============================================== ============================================== ============================================== 1. the input