SPHERICAL TRAIT IN CORRESPONDENCE ANALYSIS OF ARTIFICIAL DATA

Abstract

Besides the well-known linear or circular trait, the spherical trait is introduced in correspondence analysis of artificial data. Five types of regular polyhedrons are used as the item pattern. The trait always has three dimensions. Furthermore, solid spherical data can be constructed by adding the center and, if necessary, one or more concentric polyhedrons. Then the data set also has a linear trait representing the radius, which may compete with the spherical trait, hindering a few of the largest eigenvalues in reproducing the item pattern faithfully.