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Title: Integrating robust clustering techniques in S-PLUS
Authors: Struyf, A ×
Hubert, Mia
Rousseeuw, Peter #
Issue Date: 1997
Publisher: Elsevier science bv
Series Title: Computational statistics & data analysis vol:26 issue:1 pages:17-37
Abstract: This paper describes the incorporation of seven stand-alone clustering programs into S-PLUS, where they can now be used in a much more flexible way. The original Fortran programs carried out new cluster analysis algorithms introduced in the book of Kaufman and Rousseeuw (1990). These clustering methods were designed to be robust and to accept dissimilarity data as well as objects-by-variables data. Moreover, they each provide a graphical display and a quality index reflecting the strength of the clustering. The powerful graphics of S-PLUS made it possible to improve these graphical representations considerably. The integration of the clustering algorithms was performed according to the object-oriented principle supported by S-PLUS. The new functions have a uniform interface, and are compatible with existing S-PLUS functions. We will describe the basic idea and the use of each clustering method, together with its graphical features. Each function is briefly illustrated with an example. (C) 1997 Elsevier Science B.V.
URI: 
ISSN: 0167-9473
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Statistics Section
× corresponding author
# (joint) last author

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