Seriation Using Asymmetric Proximity Measures

The data analysis problem of ordering or sequencing a set of objects using an asymmetric proximity function is reviewed, with an emphasis on literature not generally referenced in psychology. In particular, an attempt is made to present some of the more important approaches to the asymmetric seriation task that have been developed independently under a number of different names, for instance, the triangularization of input‐output matrices, minimum feedback arc sets, maximum likelihood paired comparison ranking, majority rule under transitivity constraints, and so on. A simple numerical example that illustrates some of the basic concepts is presented in the course of the discussion.