similar to: having trouble with "R CMD INSTALL"

Dear list, I am trying to understand and use the ff package. As I had some problems saving some ff objects, and as I did not fully manage to understand the whole concept of *.ff, *.ffData and *.RData with the help of the documentation, I tried to reproduce the examples from the help of ffsave. When I ran, however : (copied from the help) message("let's create some ff objects")

Hello! I've been trying to get this right for quite a while now and fear there is an easy solution I just don't see. I did not have this problem in Linux, and I searched r-help and Google but did not find a solution, but of course I am grateful for and resources I might not have found our not understood yet. I try to parse a time stamp with time zone. I essentially just want to parse the

Does anyone know if Is there a way to manually install RSPython? I get this error when I try to run the script from my DOS prompt. V:\>R CMD INSTALL -c C:/Users/gene.leynes/Downloads/RSPython_0.7-1.tar.gz * installing to library 'C:/Users/gene.leynes/Documents/R/win-library/2.13' * installing *source* package 'RSPython' ... **********************************************

I just followed the instructions on CRAN<http://cran.r-project.org/bin/linux/ubuntu/README> to install R on an Ubuntu instance. sudo apt-get install r-base Why does it install an old version of R? Can I install version 15.1? I changed my sources.list to be a current cran mirror. I believe that I have entered the URL correctly because at first I had it wrong (there was a trailing

My apologies, I know that this is not a new problem, but I'm not sure how to find the answer I want to recursively loop over an object and trim trailing white space. When I use this function on a list of data.frame I get output like this: [1] "c(\" many spaces \", \" many spaces \")" "c(\" many spaces \", \" many spaces

Deal R , when I use the package debug, mark a function with mtrace() and enter into the browser like mechanism of debug a window displaying the code of the marked function with the current line highlighted usually appears. When I use GUIs other than ess or the standard R console sometimes this window is totally transparent so it is not possible to see any code in it. After closing/resizing

I would really like some help with understanding the panel function, in zoo. Thank you. R 15.1 and zoo 1.7-7. library(zoo) x = seq(0,3*pi,length.out=100) y = sin(x) zobj = zoo(y, x) ########################################################### ## EXAMPLE 1 - GLOBAL ARGUMENT ## This panel function works ## But, it relies on mycol, which is a global variable

Why doesn't this work? x = zoo(1:5, as.Date('2001-01-01')+1:5) x[as.Date('2001-01-05')] x[as.Date('2001-01-05')] = 0 x I think this is especially bad because it doesn't cause an error. It lets you do something to x, but then you can't see x again to see what it did. [[alternative HTML version deleted]]

** Disclaimer: I'm looking for general suggestions ** I'm sorry, but can't send out the file I'm using, so there is no reproducible example. I'm using read.table and it's taking over 30 seconds to read a tiny file. The strange thing is that it takes roughly the same amount of time if the file is 100 times larger. After re-reviewing the data Import / Export manual I think

I've been wondering what L means in the R computing context, and was wondering if someone could point me to a reference where I could read about it, or tell me what it's called so that I can search for it myself. (L by itself is a little too general for a search term). I encounter it in strange places, most recently in the "save" documentation. save(..., list = character(0L),

I thought the "apply" functions are faster than for loops, but my most recent test shows that apply actually takes a significantly longer than a for loop. Am I missing something? It doesn't matter much if I do column wise calculations rather than row wise ## Example of how apply is SLOWER than for loop: #rm(list=ls()) ## DEFINE VARIABLES mu=0.05 ; sigma=0.20 ; dt=.25 ; T=50 ;

I don't understand how this function can subset by i when i is missing.... ## My function: myfun = function(vec, i){ ret = vec[i] ret } ## My data: i = 10 vec = 1:100 ## Expected input and behavior: myfun(vec, i) ## Missing an argument, but error is not caught! ## How is subsetting even possible here??? myfun(vec) Is there a way to check for missing function arguments, *and*

I think that the "quietly" argument in "require" isn't working > require('JumboShrimp', quietly=TRUE) Warning in library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : there is no package called 'JumboShrimp' > By the way, the behavior is the same with options(warn=0) or options(warn=1) I'm using R 2.12

# Just when I thought I had the basic stuff mastered.... # This has been quite perplexing, thanks for any help ## Here's the example: db1=data.frame( olditems=c('soup','','','','nuts'), prices=c(4.45, 3.25, 4.42, 2.25, 3.98)) db2=data.frame( newitems=c('stew','crackers','tofu','goatsmilk','peanuts'))

Does anyone know how to pass a list of parameters into a function? for example: somefun=function(x1,x2,x3,x4,x5,x6,x7,x8,x9){ ans=x1+x2+x3+x4+x5+x6+x7+x8+x9 return(ans) } somefun(1,2,3,4,5,6,7,8,9) # I would like this to work: temp=c(x3=3,x4=4,x5=5,x6=6,x7=7,x8=8,x9=9) somefun(x1=1,x2=2,temp) # OR I would like this to work: temp=list(x3=3,x4=4,x5=5,x6=6,x7=7,x8=8,x9=9)

On the Mac it's pretty easy to get to a USB drive by name. For example the following command works if you have a USB drive named "MYUSB" setwd('/Volumes/MYUSB') Is there a way to do the same thing in Windows (without knowing the drive letter)? Thanks! [[alternative HTML version deleted]]

*What I want to do: *Create a windows shortcut that will start the R gui **and** simultaneously source a file *What I have already tried: *This almost works, but it's not the interactive R GUI: R --no-save --sdi -file="C:\SomePath\example.R" These open the R GUI, but doesn't recognize -f --f --file -file RGUI --no-save --sdi -file="C:\SomePath\example.R"

I've been trying to figure out how to read in a large file for a few days now, and after extensive research I'm still not sure what to do. I have a large comma delimited text file that contains 59 fields in each record. There is also a header every 121 records This function works well for smallish records getcsv=function(fname){ ff=file(description = fname) x <- readLines(ff)

I have tried a lot of ways around this, but I can't find a way to make apply work in a generalized way because it causes a failure whenever reduces the dimensions of its output. The following example is easier to understand than the question. I wish it had a "drop=TRUE/FALSE" option like the "[" (and I wish I had found the drop option a year ago, and I wish that I had 1e6

Can someone please tell me what is up with na.action in aggregate? My (somewhat) reproducible example: (I say somewhat because some lines wouldn't run in a separate session, more below) set.seed(100) dat=data.frame( x1=sample(c(NA,'m','f'), 100, replace=TRUE), x2=sample(c(NA, 1:10), 100, replace=TRUE), x3=sample(c(NA,letters[1:5]), 100, replace=TRUE),