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Disclaimer: I park links here that come up repeatedly in my own work and in my teaching. I freshen/organize very sporadically.

**My links to certain eBooks and repositories are tuned to UBC users.**

eBook repositories

- STATSnetBASE eContent portal for CRC Press.
- Their R Series has had some exciting recent additions (see below).
*Wonder if there's a UBC-tuned way to link to that collection?*

- Their R Series has had some exciting recent additions (see below).
- SpringerLink eContent portal for Springer.
- The Use R! series is especially helpful (many individual titles appear below)
- The Statistics and Computing series

Books (updated January 2014; older list below)

R Graphics, 2nd edition available via StatsNetbase by Paul Murrell, Chapman & Hall/CRC Press (2011) | author's webpage for the book | GoogleBooks search | companion R package, RGraphics, on CRAN

- * R Graphics, 1st edition, which was quite different so perhaps worth linking available via StatsNetbase by Paul Murrell, CRC Press | author's webpage for the book | GoogleBooks search

Lattice: Multivariate Data Visualization with R available via SpringerLink by Deepayan Sarkar, Springer (2008) | all code from the book | GoogleBooks search

ggplot2: Elegant Graphics for Data Analysis available via SpringerLink by Hadley Wickham, Springer (2009) | online docs (nice!) | author's website for the book, including all the code | author's landing page for the package

Data Manipulation with R available via SpringerLink by Phil Spector, Springer (2008) | author webpage | GoogleBooks search

Dynamic documents with R and knitr by Yihui Xie, part of the CRC Press / Chapman & Hall R Series (2013). ISBN: 9781482203530.

*No online access (yet?).*Reproducible Research with R & RStudio by Christopher Gandrud, part of the CRC Press / Chapman & Hall R Series (2013). ISBN: 978-1466572843. Book website | Examples and code | Book source.

*Very new, no online access (yet?).*All of Statistics: A Concise Course in Statistical Inference, available via SpringerLink, by Larry Wasserman, Springer Texts in Statistics (2004) | author's webpage for the book | GoogleBooks search

`plyr`

package for data aggregation

- The split-apply-combine strategy for data analysis, Hadley Wickham, Journal of Statistical Software, vol. 40, no. 1, pp. 1–29, 2011.

Smart editor/IDE set-ups for R programming (M = Mac OS or other *nix, W = Windows, A = both)

- RStudio (A) <–
**USE THIS unless you have a really good reason to do otherwise** - Emacs + Emacs Speaks Statistics (ESS) (A) <– I used to use this but have almost completely switched over to RStudio now.
- TextMate + R bundle (or bundles? google it) (M)
- Tinn-R (W)
- WinEdt + RWinEdt (W)
- NotePad++ + NppToR (W)
- vim + R.vim (M)

Potentially helpful links related to the editor/IDE issue (no guarantees these are good, current, etc.)

- ESS reference card
- ESS section on the R FAQ
- Good overview of setup of Emacs, ESS, Tinn-R, Rcmdr on Windows (from Scott Hyde, BYU-H)
- Tutorial on installing Tinn-R (from Bioinformatics in Arkansas)
- Carbon Emacs Package = a Mac-friendly distribution of GNU Emacs which includes ESS
- Vincent Goulet's Emacs distributions (Windows and Mac OS) w/ ESS, AUCTeX, and other goodies

R style, coding conventions, and philosophy

- SOURCE IS REAL!
- Spreadsheets are overused: Spreadsheet Addiction by Patrick Burns
- Google's R style guide *and the discussion thereof within the R community
- Hadley Wickham's adaptation of the Google style and his rubric for marking R code (see last page FIX)
- Karl Broman's (Wisconsin) coding practices lecture
- Chapter 2 in S Poetry (from Patrick Burns)
- Martin Maechler's keynote from useR 2004
- R Coding Conventions (from Henrik Bengtsson, Lund University)
- Blog thread on R style (from a post by Andrew Gelman, Columbia)

eBooks (your mileage may vary depending on your personal or institutional subscription coverage)

- The R Book by Michael Crawley, Wiley (2007)
- Software for Data Analysis: Programming with R by John Chambers. Springer (2008)
- A Handbook of Statistical Analyses Using R by Brian Everitt and Torsten Hothorn, CRC Press
- Handbook of Statistical Analyses using S-Plus, Second Edition by Brian Everitt, CRC Press
R Programming for Bioinformatics by R Gentleman, CRC Press

All of Nonparametric Statistics by Larry Wasserman, Springer (2006) | alternate myiLibrary link | GoogleBooks search (FIX: google search link not correct)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Hastie, Tibshirani, & Friedman, Springer (2009)

Statistical DNA Forensics by Wing Kam Fung and Yue-Qing Hu, Wiley (2008)

Statistics and Data with R by Yosef Cohen and Jeremiah Y. Cohen, Wiley (2008)

Statistics for Microarrays by Ernst Wit and John McClure, Wiley (2004)

Nonparametric Regression Methods for Longitudinal Data Analysis by Wu Hulin, Zhang Jin-Ting, Wiley (2006)

Other

- Help for R: a great collection of R related links, esp. for helping and searching (from Jonathon Baron, U Penn)
- A short list of the most useful R commands (from William Revelle, Northwestern)
- Evaluating the design of the R language, via Davor Cubranic: “It's an analysis of R as a
*programming language*, done by computer language designers. This is the link I send to my friends from CS grad school.”) - R programming for those coming from other languages by John Cook, via Davor Cubranic.