Note: This original post has been modified to make it easier to find the resources in the thread and to compile them into one location. If you want to view the post as Tart left it click on the spoiler at the end of the thread

Hello All,
Please add to this post useful links, recommendation for books and so on. Thank you all.

Editors:

RStudio - One of the best IDEs for working with R today. It is being developed at an amazing rate and new features are being added all the time.

Emacs + ESS - If you're an Emacs user then using the ESS (Emacs Speaks Statistics) plugin is a natural choice. Emacs is a very powerful editor and ESS adds support for R syntax and easily allows you to create a buffer for an R session.

Rkward - It is available in the repositories for most Linux distros. You can run it on Windows and/or Macs but takes a little bit more work.

Tinn-R (Windows) - The former king. It seems to be out of fashion now a days.

There is more to add but I haven't got around to updating this post yet. View the spoiler for more.

Spoiler:

Hello All,
Please add to this post useful links, recommendation for books and so on. Thank you all.

These are some links if you are just starting with R I hope they will help you, others may find them useful too.

Getting started in R, I've found Michael J. Crawley's "Statistical Computing, An Introduction to Data Analysis using S-Plus" very helpful. Crawley's newer "The R Book" may be better for R users, though I haven't seen it. Cheers, Pete

"Modern Applied Statistics with S" by Venables and Ripley - classic, must have for everyone.

If you are doing linear modeling then I think that flowing two books are a must have. "Linear Models with R" and "Extending the Linear Models with R" by Faraway. Books very well written, full of examples, advices, recommendations and tricks.

"Data Analysis using Regression and Multilevel/Hierarchical Models" by Gelman and Hill. I just started reading this book, this is a book about multilevel modeling, but all examples are in R. Authors show you how to apply theory in R. Really nice.

If you are working with graphics, then this book will help you a lot "R Graphics" by Murrell. It doesn't tell you how to create certain plot. It describes how graphics works. Especially tricky lattice/Trellis graphics.

"Statistical Computing with R" by Rizzo this book covers statistical methods using R quite well. It is not specialized, just gives overview of essential methods.

"Data Manipulation with R (Use R)" by Spector - this one on my wish list. It looks like another must have :-). UPDATE: I have this book now, and it is very useful. Definitely mast have.

Last edited by Tart; 03-30-2009 at 09:24 AM.

Many people would sooner die than think. In fact they do. - B. Russell

http://rattle.togaware.com/ - Rattle: Gnome Cross Platform GUI for Data Mining using R. Didn't play with it yet, but it looks interesting.

Rattle (the R Analytical Tool To Learn Easily) is a data mining toolkit used to analyse very large collections of data. Rattle presents statistical and visual summaries of data, transforms data into forms that can be readily modelled, builds both unsupervised and supervised models from the data, presents the performance of models graphically, and scores new datasets.

Through a simple and logical graphical user interface based on Gnome, Rattle can be used by itself to deliver data mining projects. Rattle also provides an entry into sophisticated data mining using the open source and free statistical language R.

Rattle runs under GNU/Linux, Macintosh OS/X, and MS/Windows. The aim is to provide an intuitive interface that takes you through the basic steps of data mining, as well as illustrating the R code that is used to achieve this. Whilst the tool itself may be sufficient for all of a user's needs, it also provides a stepping stone to more sophisticated processing and modelling in R itself, for sophisticated and unconstrained data mining.

Many people would sooner die than think. In fact they do. - B. Russell