Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
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Authors: Anthony Recchia
Title: Contiguity-Constrained Hierarchical Agglomerative Clustering Using SAS
Abstract: Hierarchical clustering is one of the most basic methods for partitioning a set of objects into clusters of similar objects. In standard clustering analysis, every pair of objects or clusters is eligible to be joined during each iteration of the clustering algorithm. However, there are circumstances under which it would be preferable to limit this eligibility. One obvious situation is when the objects of interest are geographical regions which should only be allowed to merge when they are contiguous. The goal here is to demonstrate a SAS macro that will perform the agglomerative version of hierarchical clustering while providing the user with an intuitive means of imposing a contiguity constraint.

Page views:: 5771. Submitted: 2009-08-13. Published: 2010-02-02.
Paper: Contiguity-Constrained Hierarchical Agglomerative Clustering Using SAS     Download PDF (Downloads: 6244)
Supplements: SAS macro Download (Downloads: 2052; 36KB) SAS example code from the paper Download (Downloads: 1772; 10KB)

DOI: 10.18637/jss.v033.c02

This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.