Resources for BUGS:

BUGS ( Bayesian inference Using Gibbs Sampling) is computer software for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods, and is implemented as WinBugs (graphical user interface Windows only) or as OpenBugs (Linux/Windows/Mac OS)

• BUGS Homepage
  
• WinBugs (Windows) Downloads, FAQS, Examples
  
• Open Bugs (Linux/Windows) Downloads, FAQS, Examples
  
• WinBugs: The Movie Demonstrates where to point and click using the GUI version of Winbugs.
  
• Running WinBugs from R and from other programs
  
• Running OpenBugs from R (Windows only)
  
• coda

Resources for R:

R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. Contributed packages provide further extensibility and allow one to create input data, scripts, initial values and run WinBugs code from R. MCMC diagnostics are available using the R package Coda.

R Project Site: The R Project's homepage with Documentation, Downloading R, FAQs, more (subset given below)

An Introduction to R (the most up-to-date version of the Intro notes)

• R CRAN SITE (downloads, documentation, and more)
  
• FAQs (please read before posting a question!)
  
• Packages (contributed packages for R)
  
• R reference card [pdf (59k, 1 pg)] (J Baron)
  
• Writing R extensions [pdf (425k; 69 pgs)] (Explanations of writing packages and calling C from R)

• Using R for data analysis and graphics [pdf (693k; 112 pgs)] (JH Maindonald)

Books

• WN Venables, DM Smith and the R Development Core Team (2004) An introduction to R. [Amazon ]
• P Dalgaard (2002) Introductory statistics with R, Springer-Verlag, New York
• WN Venables and BD Ripley (2002) Modern applied statistics with S, 4th edition. Springer-Verlag, New York. [Online complements]
• WN Venables and BD Ripley (2000) S programming. Springer-Verlag, New York.
• JM Chambers (1998) Programming with data : A guide to the S Language. Springer-Verlag, New York.
• JM Chambers and TJ Hastie (eds) (1991) Statistical models in S. Chapman & Hall, New York.

ESS (Emacs Speaks Statistics) provides a common, generic and useful interface to many statistical packages through Emacs. It currently has interfaces to S, R, XLisp-Stat, and SAS, with other statistical languages such as Stata, SPSS, and Fiasco slated for implementations in the future.

ESS Reference Card (pdf)

Emacs Quick Reference Card

Emacs Quick Tutorial

Gnu Emacs Site and XEmacs Site

Other Useful Software for Windows (Ghostview, Acroread, Emacs, etc)