Chapter 9Principal components analysis
In Section 1.1, we considered a 
-dimensional random vector 
with 
and covariance matrix 
. If
is the eigenvalue–eigenvector decomposition for the covariance matrix, we saw that 
could be decomposed as
for 
zero mean, uncorrelated random variables having 
. The 
provide a new set of variables that are called the principal components of 
. One may, for example, ...
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