Page 197 - Computational Statistics Handbook with MATLAB

184 Computational Statistics Handbook with MATLAB

In the Computational Statistics Toolbox, we include several functions that
implement some of the algorithms and graphics covered in Chapter 5. These
are summarized in Table 5.3.

T
A
A
TA AB BL LE L E 5.3 5.3
T
T
E
5.3
5.3
E
B
B
L
List of Functions from Chapter 5 Included in the
Computational Statistics Toolbox
Purpose MATLAB Function
Star Plot csstars
Stem-and-leaf Plot csstemleaf
Parallel Coordinates Plot csparallel
Q-Q Plot csqqplot
Poissonness Plot cspoissplot
Andrews Curves csandrews
Exponential Probability Plot csexpoplot
Binomial Plot csbinoplot
PPEDA csppeda
csppstrtrem
csppind

5.6 Further Reading
One of the first treatises on graphical exploratory data analysis is John
Tukey’s Exploratory Data Analysis [1977]. In this book, he explains many
aspects of EDA, including smoothing techniques, graphical techniques and
others. The material in this book is practical and is readily accessible to read-
ers with rudimentary knowledge of data analysis. Another excellent book on
this subject is Graphical Exploratory Data Analysis [du Toit, Steyn and Stumpf,
1986], which includes several techniques (e.g., Chernoff faces and profiles)
that we do not cover. For texts that emphasize the visualization of technical
data, see Fortner and Meyer [1997] and Fortner [1995]. The paper by Weg-
man, Carr and Luo [1993] discusses many of the methods we present, along
with others such as stereoscopic displays, generalized nonlinear regression
using skeletons and a description of d-dimensional grand tour. This paper
and Wegman [1990] provide an excellent theoretical treatment of parallel
coordinates.
The Grammar of Graphics by Wilkinson [1999] describes a foundation for
producing graphics for scientific journals, the internet, statistical packages, or

© 2002 by Chapman & Hall/CRC