Two-mode multi-partitioning

Authors:
Roberto Rocci;Maurizio Vichi
Affiliations:
University "Tor Vergata", Rome, Italy;Department of Statistics, Probability and Applied Statistics, University "La Sapienza", P.le A. Moro 5, I-00185 Roma, Italy
Venue:
Computational Statistics & Data Analysis
Year:
2008

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Abstract

New methodologies for two-mode (objects and variables) multi-partitioning of two way data are presented. In particular, by reanalyzing the double k-means, that identifies a unique partition for each mode of the data, a relevant extension is discussed which allows to specify more partitions of one mode, conditionally to the partition of the other one. The performance of such generalized double k-means has been tested by both a simulation study and an application to gene microarray data.