tclust: An R Package for a Trimming Approach to Cluster Analysis

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Authors Heinrich Fritz, Luis Angel García-Escudero, Agustín Mayo-Íscar
Journal/Conference Name Journal of Statistical Software
Paper Category
Paper Abstract Outlying data can heavily influence standard clustering methods. At the same time, clustering principles can be useful when robustifying statistical procedures. These two reasons motivate the development of feasible robust model-based clustering approaches. With this in mind, an R package for performing non-hierarchical robust clustering, called tclust, is presented here. Instead of trying to “fit” noisy data, a proportion α of the most outlying observations is trimmed. The tclust package efficiently handles different cluster scatter constraints. Graphical exploratory tools are also provided to help the user make sensible choices for the trimming proportion as well as the number of clusters to search for.
Date of publication 2012
Code Programming Language R

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