Clustering directional data through depth functions. (English) Zbl 07734167
Summary: 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.
MSC:
| 62-08 | Computational methods for problems pertaining to statistics |
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