Page 202 - Computational Statistics Handbook with MATLAB

Chapter 5: Exploratory Data Analysis 189

matrix and use the boxplot function to compare normal versus
diabetic patients.
5.21. To explore the shading options in MATLAB, try the following code
from the documentation:
% The ezsurf function is available in MATLAB 5.3
% and later.
% First get a surface.
ezsurf('sin(sqrt(x^2+y^2))/sqrt(x^2+y^2)',...
[-6*pi,6*pi])
% Now add some lighting effects:
view(0,75)
shading interp
lightangle(-45,30)
set(findobj('type','surface'),...
'FaceLighting','phong',...
'AmbientStrength',0.3,'DiffuseStrength',0.8,...
'SpecularStrength',0.9,'SpecularExponent',25,...
'BackFaceLighting','unlit')
axis off
5.22. The bank data contains two matrices comprised of measurements
made on genuine money and forged money. Combine these two
matrices into one and use PPEDA to discover any clusters or groups
in the data. Compare your results with the known groups in the data.
5.23. Using the data in Example 5.27, do a scatterplot matrix of the original
sphered data set. Note the structures in the first four dimensions. Get
the first structure and construct another scatterplot matrix of the
sphered data after the first structure has been removed. Repeat this
process after both structures are removed.
5.24. Load the data sets in posse. These contain several data sets from
Posse [1995b]. Apply the PPEDA method to these data.

© 2002 by Chapman & Hall/CRC