  In this work, we present a minimum entropy analysis scheme for variable
selection and preliminary data analysis. The variable selection can be achieved
by the increasing preference of variables. We show such a preference to has a
unqiue form, which is given by the entropy of models associated with variables.
Evaluating the entropy provides a complete ranking scheme of variables. This
scheme not only indicates preferred variables but also may reveal the system's
nature and properties. We illustrate the proposed scheme to analyze a set of
geological data for three carbonate rock units in Texas and Oklahoma, and
compare to the discriminant function analysis. The result suggests this scheme
to provide a quick and robust analysis, and the use in data analysis is
promising.
