A method for computation of dominance relations
and for construction of their corresponding
hierarchical structures is presented. It is shown that
variance can be computed from the squared pairwise
differences between scores and that dominance
indices are actually linear transformations of variances.
The interpretation of variance as a quantitative
measure of information is suggested and conceptual
partition of variance into components associated
with relational spaces is proposed. The
link between dominance and variance allows integration
of the mathematical theory of information
with least squares statistical procedures without recourse
to logarithmic transformations of the data.
Krus, David J.; Ceurvorst, Robert W..
Dominance, information, and hierarchical scaling of variance space.
Retrieved from the University of Minnesota Digital Conservancy,
Content distributed via the University of Minnesota's Digital
Conservancy may be subject to additional license and use
restrictions applied by the depositor.