Chapter 2 Introduction
2.1 What is R?
R was not designed to be a bona-fide programming language. It is an evolution of the S language, developed at Bell labs (later Lucent) as a wrapper for the endless collection of statistical libraries they wrote in Fortran.
As of 2011, half of R’s libraries are actually written in C.
2.2 The R Ecosystem
A large part of R’s success is due to the ease in which a user, or a firm, can augment it. This led to a large community of users, developers, and protagonists. Some of the most important parts of R’s ecosystem include:
CRAN: a repository for R packages, mirrored worldwide.
Task Views: part of CRAN that collects packages per topic.
Bioconductor: A CRAN-like repository dedicated to the life sciences.
Neuroconductor: A CRAN-like repository dedicated to neuroscience, and neuroimaging.
Books: An insane amount of books written on the language. Some are free, some are not.
The Israeli-R-user-group: just like the name suggests.
Commercial R: being open source and lacking support may seem like a problem that would prohibit R from being adopted for commercial applications. This void is filled by several very successful commercial versions such as Microsoft R, with its accompanying CRAN equivalent called MRAN, Tibco’s Spotfire, and others.
2.3 Bibliographic Notes
You can also consult the Introduction chapter of the MASS book (Venables and Ripley 2013).
2.4 Practice Yourself
Venables, William N, and Brian D Ripley. 2013. Modern Applied Statistics with S-Plus. Springer Science & Business Media.