Old issues of the journals predecessor, R News, can be found here.

Good reading!

General

The R Journal A link to the R Journal, a peer-reviewed and open access journal concerning R and related topics in statistical computing etc.

USGS/NPS R Short Course: A link to materials of the earlier mentioned short course in R held by USGS and NPS.

RSeek.org: A search engine specific for R related queries based on Google’s Custom Search.

StatsRus (alias RTips): “… is not a substitute for R documentation, just a list of things I’m using to remember what I read in the email list.” I found it quite an impressive list covering lots of FAQ concerning data input/output, data frames, matrices, graphs, model fitting and many more.

Short Reference Card: A neat reference to quickly look up essential functions/commands. Function lists are also available for regression and time series.

Ecology related

R Labs for Vegetation Ecologists: A series of lab materials and exercises from Montana State University about modeling species distributions using generalized linear and additive models, performing principal component and correspondence analysis, and more.

simecol – Ecological Models with R: Nice package which allows users to implement basic and more advanced ecological models in R.

R-sig-ecology: Mailing list / discussion forum for questions specific to the use of R for ecological and environmental data analysis.

R-taskhelp: Ecology: Unmaintained? Last entry from 2000.

Personally, I started learning R through Michael Crawley’s book “Statistics: An Introduction using R” (Wiley, 2005; ISBN 0-470-02297-3). I found it very useful to get started on data analysis with R.

“The R Book” (Wiley, 2007; ISBN 978-0-470-51024-7) published by the same author is a more comprehensive work. Both text books still require you to read up on the more specialist methods of your field, but they provide a good base (I don’t get promotions by the way ).

R is a language and environment for statistical computing and graphics. It shares similarities with the S system, which was developed at Bell Laboratories by John Chambers. More information on R can be found on the web site of the R – project.

Apart from being freely available under the GNU public license the R software is a powerful tool when it comes to data analysis and graphics. A wide range of add-on packages are available to perform a great diversity of statistical analysis and graphical tasks (visit the web page of the Comprehensive R Network for more information).