Computing
R Statistical Computing Package
We will primarily be using the R statistical computing package in
this course. R is a freely available, open-source version of
S/S-plus. While most S/S-plus code will run in R, there are several
differences. Therefore, it is recommended that all computing for the
course be done in R.
Previous experience with statistical computing is a prerequisite for
this course. However, knowledge of R or S/S-plus is not expected.
Demonstrations of analyses in R will be given during lecture, and
example code will be provided for lecture examples as well as with
some homework assignments. In addition to this example code, it is
highly recommended that the R manual
and online help system be used as a supplement.
R is available in the Department of Statistics Student Computer
Laboratory, which is open only to Statistics students. R can also be
downloaded
to personal computers for no cost. Students who do not have access to
the computer lab and have difficulty accessing R should speak to
the instructor.
Students using R on their personal computers may want to download Tinn-R, an R code editor --
see the installation and configuration instructions (prepared by Dale Rhoda).
NOTE: You do not need
to use Tinn-R to edit R code; you can use Notepad, as well as other text
editors available in Windows.
WinBUGS/OpenBUGS
In addition to R, we will be using WinBUGS, a
software package for fitting complex statistical models using Markov chain Monte
Carlo (MCMC) methods. In particular, we will be using a freely
available, open-source version of WinBUGS, called OpenBUGS. OpenBUGS
can be called directly from R using the BRugs R package.
OpenBUGS software is also available in the Department of Statistics
Student Computer Laboratory and can be downloaded
to students' personal computers. An overview of WinBUGS and many examples
can be found in the WinBUGS
manual.