Preference structure analysis: A nonmetric approach

摘要

A nonmetric procedure is suggested to analyze the structure of preferences among multivariate groups. This data analysis technique enables one to compete with discriminant analysis as a special case as well as with some other more complicated problems. The goal of the article is mainly twofold: 1.1. to suggest a nonmetric procedure in which goodness of discrimination is higher than or equal to that of Fisher's discriminant function (FDF) (the number of misclassification errors for given data will be less or equal to that obtained by FDF while using the nonmetric procedure);2.2. to exemplify the fact that very different discriminant functions could yield the very same number of errors. The latter issue was revealed due to the apparent drawback of non-uniqueness of the discriminant function (solution) obtained by our procedure. Non-uniqueness usually seems to be a drawback, nevertheless it might be an advantage, as exemplified later by real examples. Non-uniqueness is a common property of data analysis methods.