Bayesian Statistics: Software Support
This page has a reference character. It links the student with the sources
useful for learning the languages and points to the third-party packages,
manuals, resources, and programs.
In this course we will mostly use two software packages: Matlab and
Bugs. Matlab is a language of choice for communication among
It is easy to grasp, it is powerful, and it has a wealth of packages and support.
Bugs/WinBugs is a free stand-alone package for MCMC inference.
It has easy sintax and a superb support.
For PhD students in Statistics (quite a few at ISyE) the R package is recommended.
R is a language of statistics. R is a free S (SPlus) clone and
is supported by an army of statisticians. For a student who had not been exposed to
S language before R may be on the difficult side.
R keeps objects in its internal code making communication with other packages
and outside world cumbersome for a novice.
At occasions we will use Wolfram's
mathematica when exact analytic solutions
are needed in nontrivial situations (use of special functions, nonlinear equations, etc).
Matlab (Matrix laboratory) is an
interactive software system for numerical computations and
graphics. As the name suggests, Matlab is especially designed for matrix and vector computations:
solving systems of linear equations, computing eigenvalues and eigenvectors, factoring matrices,
and so forth. In addition, it has a variety of graphical capabilities, and can be extended through
programs written in its own programming language. Tons of addon packages are available either
as commercial Matwork's products or as a freely available user contributions.
Numerous resources for Matlab are available online.
BUGS is freely available software for the constructing Bayesian statistical models
and evaluating them using Markov-Chain Monte-Carlo (MCMC) methods.
BUGS and WINBUGS are distributed freely and are the result of many years
of development by a team of statisticians and programmers at the Medical
research Council Biostatistics Research Unit in Cambridge,
see Bugs Project .
Models are represented by a flexible language, and there is also a graphical feature, DOODLEBUGS,
that allows users to specify their model in terms of a directed graph.
For complex models the latter can be extremely useful.
These manuals are for original BUGS. The examples could be readily
modified to WinBUGS.
R is a free statistical programming language based on the S
programming language. It provides numerous libraries covering
the state-of-art statistical research and is powerful and extensible.
S is a base for R. It has its origins in the AT&T Bell Labs.
Beginning in 1976, the S
programming language was developed at Bell Labs by John Chambers
and collaborators. Version 1 was running on Honeywell mainframes, Version 2 (1980)
added Unix support, Version 3 (1988) added functions and objects, and
Version 4 (1998) added full support for object-oriented design.
Beginning in 1993, Bell Labs issued an exclusive license to
StatSci (later MathSoft). S-Plus
is Mathsofts commercial implementation of S, and the only way
the language is available outside Lucent (unfortunatelly).
The free clone to S, R, was started by Robert Gentleman
and Ross Ihaka of the University
of Auckland. It is now an open
source project that involves hundreds of volunteers from around the world.
The development of R is guided through the Comprehensive R Archive
network, and full source code, binaries and documentation are
available free at the CRAN web
Numerous resources for R, S and S-Plus are available online,
- John Verzani's excellent
SimpleR : Introduction to Statistics via R.
- Emmanuel Paradis
R for Beginners.
- Faraway's Course on Practical
Regression and Anova
You will need
faraway.zip archive to "Install packages from local zip file(s)" in R and call library(faraway),
in order to reproduce examples from the manuscript.
R. ZIP archive that expands to HTML type tutorial.
- R Language Short Companion,
Version 1.2, by Marc Vandemeulebroecke.
- Using R, by J.H. Maindonald from
- The Carnegie-Mellon archive of S
- ISDSs online S-Plus tutorial
- William Revelle's A Short Guide
- Barron and Lis Use
of R for psychology experiments and questionnaires.
Also R reference card by
- Venables and Ripley, Modern
Applied Statistics with S-PLUS, 3rd ed., London:
Springer-Verlag, 1999. ISBN 0-387-98825-4.
Also, R complements
supplement to Venables and Ripley (1999).
- Venables and Ripley, S
Programming, 3rd ed., London: Springer-Verlag, 2000. ISBN
MSBNx is a free Microsoft Windows software application that supports the creation,
manipulation and evaluation of Bayesian probability models.
Models are represented as a graph or diagram.
At the present time, MSBNx only supports discrete distributions for its model variables.
Last Updated: July 27, 2004.
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