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CLUSKEXT: CLUstering model for SKew-symmetric data including EXTernal information

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Abstract

A CLUstering model for SKew-symmetric data including EXTernal information (CLUSKEXT) is proposed, which relies on the decomposition of a skew-symmetric matrix into within and between cluster effects which are further decomposed into regression and residual effects when possible external information on the objects is available. In order to fit the imbalances between objects, the model jointly searches for a partition of objects and appropriate weights which are in turn linearly linked to the external variables. The proposal is fitted in a least-squares framework and a decomposition of the fit is derived. An appropriate Alternating Least-Squares algorithm is provided to fit the model to illustrative real and artificial data.

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Acknowledgments

The author wishes to thank the associate editors and the anonymous referees for their constructive comments and suggestions which greatly improved the quality of the paper.

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  1. Dipartimento di Scienze Statistiche, Sapienza University of Rome, Pl. Aldo Moro, 5, 00185, Roma, Italy

    Donatella Vicari

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  1. Donatella Vicari
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Correspondence to Donatella Vicari.

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Vicari, D. CLUSKEXT: CLUstering model for SKew-symmetric data including EXTernal information. Adv Data Anal Classif 12, 43–64 (2018). https://doi.org/10.1007/s11634-015-0203-0

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  • DOI: https://doi.org/10.1007/s11634-015-0203-0

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