R resource page

R is a language and environment for statistical computing and graphics. For comprehensive information visit the home page of the R Project for Statistical Computing.

Here are direct links to downloading R and to instructions on how to install R under Windows (you can find instructions also for other operating systems on the R Project home page).

If you are using Windows, we recommend installing Tinn-R, as well, which provides a very useful interface to work with R. You can download the latest version of Tinn-R from its sourceforge page. However, the new versions seem to have problems with 'send selection', I therefore suggest to download and install the older version 1.19.4.7, which did not have this problem yet.

If you are using Linux/Unix, we recommend installing RKWard, which provides a very nice frontend to R under this platform. (It also has a version for Windows, but that is reported to have some bugs).

For a start, we recommend reading An Introduction to R (also available in pdf). Some sections are not relevant for the current course. We recommend reading the following sections: Sections 1-3, 5.1-5.4, 5.7.1, 5.8-5.9, 6, 7.1-7.2, 7.4, 9, 10.1, 10.3, 12.1-12.2, 12.4-12.6, 13. ~50 pages total.

You can download a concise "reference card" that is useful to have around when writing R code.

A large number of books have been written on R (and its elder sister, S). For a good overview we recommend: William N. Venables and Brian D. Ripley. S Programming. Springer, New York, 2000.