Hierarchical Clustering by Means of Model Grouping

  • Claudio Agostinelli
  • Paolo Pellizzari
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


In many applications we are interested in finding clusters of data that share the same properties, like linear shape. We propose a hierarchical clustering procedure that merges groups if they are fitted well by the same linear model. The representative orthogonal model of each cluster is estimated robustly using iterated LQS regressions. We apply the method to two artificial datasets, providing a comparison of results against other non-hierarchical methods that can estimate linear clusters.


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Copyright information

© Springer Berlin · Heidelberg 2006

Authors and Affiliations

  • Claudio Agostinelli
    • 1
  • Paolo Pellizzari
    • 2
  1. 1.Dipartimento di StatisticaUniversità Ca’ FoscariVeneziaItalia
  2. 2.Dipartimento di Matematica ApplicataUniversità Ca’ FoscariVeneziaItalia

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