Friday, April 15, 2011

Best editor for R (in Windows)

Here are my current picks for best editors in R, where "best" means 
  • free, 
  • easy to install, and 
  • intuitive to use.

[For these editors, there might be versions for MacOS and Unix, but if you are going to run the programs from Doing Bayesian Data Analysis that call BRugs, then you'll need to run the 32-bit Windows version of R and (I presume) run the editor in Windows too. But if you don't use BRugs, and instead use JAGS with rjags, then you should get the version of the editor that is appropriate for your operating system.]

1. RStudio

2. Notepad++ with the add-on NppToR
Get Notepadd++ from http://notepad-plus-plus.org/ and 
get the NppToR add-on from http://sourceforge.net/projects/npptor/

3. Tinn-R
Although mentioned in the textbook, Tinn-R does not install seamlessly for a lot of users.

Additional suggestions or comments about these editors are welcome.

4 comments:

Jeromy Anglim said...

Yep. R Studio would be my pick of the bunch for someone new to R and new to programming.

That said, there are good arguments to get comfortable with a particular editor and then adopt tools to integrate with R. For those wanting to adopt a more serious editor, I'd recommend Vim with the Vim R plugin or Emacs with ESS; a third decent option is Eclipse with Stat ET.

I'm currently using Vim with Vim-R, but it has required a fair amount fiddling to get working the way that I like. I would only recommend Vim-R to someone who was already using Vim or keen to learn Vim.

René said...

on linux, ubuntu ... : best editors (IMO) are kate, Rkward

Fred said...

Another free, easy to install, and intuitive to use R-IDE I would recommend is RKWard. It's open source, availible for Windows, Mac and Linux, and it's being actively developed.

John K. Kruschke said...

Dear Fred: Thanks for pointing out RKWard. It would be nice if RKWard included Bayesian analyses in its menu, not just frequentist! In particular, it might be easy for the RKWard developers to include the Bayesian two-group comparison program from http://www.indiana.edu/~kruschke/BEST/