A two‐step procedure for clustering time varying data
Katarina Košmelj · Journal of Mathematical Sociology · 1986
The aim of this paper is to enlarge the usual domain of cluster analysis. A procedure for clustering time varying data is presented which takes into account the time dimension with its intrinsic properties. This procedure consists of two steps. In the first step a dissimilarity between variables is defined and the dissimilarity matrix is calculated for each unit separately. In the second step the dissimilarity between units is calculated in terms of the dissimilarity matrices defined in the first step. The dissimilarity matrix obtained is the base for a suitable clustering method. The procedure is illustrated on an empirical example.