Clustering of Variables Based on Watson Distribution on Hypersphere: A Comparison of Algorithms

• Type: Article in International Scientific Journal
• Date: 2015

Authors

Adelaide Figueiredo (Author) FEP; Paulo Gomes (Author) Other

Journal

Title: Communications in Statistics Part B: Simulation and Computation

Vol. 44

Pages: 2622-2635

ISSN: 0361-0918

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Scientific classification

FOS: Natural sciences > Mathematics

CORDIS: Physical sciences > Mathematics > Statistics

Other information

Authenticus ID: P-00G-DZB

DOI: 10.1080/03610918.2014.901353

Abstract (EN): We consider n individuals described by p variables, represented by points of the surface of unit hypersphere. We suppose that the individuals are fixed and the set of variables comes from a mixture of bipolar Watson distributions. For the mixture identification, we use EM and dynamic clusters algorithms, which enable us to obtain a partition of the set of variables into clusters of variables.Our aim is to evaluate the clusters obtained in these algorithms, using measures of within-groups variability and between-groups variability and compare these clusters with those obtained in other clustering approaches, by analyzing simulated and real data.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 14