Graphics Programs Reference
In-Depth Information
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0.08
0.06
2
9
1
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10
3
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7
Sample No.
Fig. 9.4
Output of the cluster analysis. The dendrogram shows clear groups consisting
of samples 1, 2, 8 to 10 (the magmatic source rocks), samples 3 to 5 (the magmatic dyke
containing ore minerals) and samples 6 and 7 (the sandstone unit).
source rocks), samples 3 to 5 (the the hydrothermal vein) and samples 6
and 7 (the sandstone). One way to test the validity of our clustering result is
the
cophenet correlation coeffi cient
. The closer this coeffi cient is to one, the
better is the cluster solution. In our case, the results
cophenet(Z,Y)
ans =
0.7579
look convincing.
9.4 Independent Component Analysis (by N. Marwan)
The principal component analysis (PCA) is the standard method for separat-
ing mixed signals. Such analysis provides signals that are linearly uncor-
related. This method is also called
whitening
since this property is char-
acteristic for white noise. Although the separated signals are uncorrelated,
