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arXiv · 2206.10447

Depth-based clustering analysis of directional data

Giuseppe Pandolfo·Antonio D'ambrosio
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Abstract

A new depth-based clustering procedure for directional data is proposed. Such method is fully non-parametric and has the advantages to be flexible and applicable even in high dimensions when a suitable notion of depth is adopted. The introduced technique is evaluated through an extensive simulation study. In addition, a real data example in text mining is given to explain its effectiveness in comparison with other existing directional clustering algorithms.

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Giuseppe Pandolfo, Antonio D'ambrosio. 2022-06-21. Depth-based clustering analysis of directional data. https://arxiv.org/abs/2206.10447

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