Abstract
In this presentation a brief survey is presented of the relative merits of two alternative approaches to the problem of modelling dependence for categorical variables when they have more than a few categories. The first approach is categorical regression with optimal scaling. The other technique is nonsymmetric(al) correspondence analysis. On a very general level, it will be shown to what an extent the techniques are similar and different.
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