Hi Ted,
The clustering code computes this value for cluster radius. Currently,
it is done with a running sums approach (s^0, s^1, s^2) that computes
the std of each vector term using:
Vector std = s2.times(s0).minus(s1.times(s1)).assign(new
SquareRootFunction()).divide(s0);
For CDbw, they need a scalar, average std value, and this is currently
computed by averaging the vector terms:
double d = std.zSum() / std.size();
The more I read about it; however, the less confident I am about this
approach. The paper itself seems to indicate a covariance approach, but
I am lost in their notation. See page 5, just above Definition 1.
www.db-net.aueb.gr/index.php/corporate/content/download/227/833/file/HV_poster2002.pdf
