An Introduction to R
by W. N. Venables, D. M. Smith
Publisher: Network Theory 2008
Number of pages: 100
This manual provides a comprehensive introduction to R, a software package for statistical computing and graphics. R supports a wide range of statistical techniques, and is easily extensible via user-defined functions written in its own language, or using dynamically loaded modules written in C, C++ or Fortran. One of R's strengths is the ease with which well-designed publication-quality plots can be produced.
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by Julian J. Faraway
The emphasis of this text is on the practice of regression and analysis of variance. The objective is to learn what methods are available and when they should be applied. Many examples are presented to clarify the use of the techniques.
by Hadley Wickham - O'Reilly Media
This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham's package development philosophy. You'll work with devtools, roxygen, and testthat, a set of R packages.
by Norman Matloff - UC Davis
This book is for those who wish to write code in R, as opposed to those who use R mainly for a sequence of separate, discrete statistical operations. The reader's level of programming background may range from professional to novice.
by Patrick Burns - Burns Statistics
If you don't know of 'The R Inferno', this revised edition is a book-length (intermediate level) explanation of a few trouble spots when using the R language. If you are using R and you think you're in hell, this is a map for you.