rkward

R-GUI for linux users.

http://rkward.sourceforge.net/

Looks much better than Rcommander or JGR.

gedit plug-in of R

http://sourceforge.net/projects/rgedit/

How to install:

To install, extract the RgeditXX.tar.bz2 archive somewhere and copy the contents of the resulting folder into to your ~/.gnome2/gedit/plugins folder (please note the "." dot; create this folder if necessary). Now, your ~/.gnome2/gedit/plugins folder should also contain:

RCtrl <- this is a folder
RCtrl.gedit-plugin
RCtrl.preferences
RCtrl.py ReadMe.txt <- this ReadMe.txt file

Then activate the "R Integration" plug-in from gedit.

R: Tables to Graphs

http://tables2graphs.com/

Reading Large datasets in R: filehash

Theoretically, the package 'filehash' makes R handle a large dataset by allowing a hard-disk space instead of a ram area for a dataset loading. I've tested this package with a 1G Stata-format dataset. It didn't work well. Anyway, here is howto:

(1) Install 'filehash'

> install.packages('filehash')
> library(filehash)

(2) Set an environment for the large dataset you'd like to use

> dumpDF(read.csv("largedata.csv"), dbName="dbname")
> envname <- db2env(db="dbname")

(3) Analyze with the environment

> with(envname, lm(y~x))

* envname & dbname can be any name you like.

filehash manual; howto by Yu-Sung Su