@article{c3bbfd75514949b7942c9fdc663836d6,
title = "Clustering of Variables Based on Watson Distribution on Hypersphere: A Comparison of Algorithms",
abstract = "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.",
keywords = "Hierarchical, cluster, Dynamic, components, Variable, preference, EM, em, Watson, analysis, distribution, component, sphere, maximum-likelihood, segmentation, clustering, model, consumers, clusters, Principal, algorithm",
author = "Adelaide Figueiredo and Paulo Gomes",
note = "ISI Document Delivery No.: CM2NF Times Cited: 0 Cited Reference Count: 30 Figueiredo, Adelaide Gomes, Paulo ERDF European Regional Development Fund through the COMPETE Programme; National Funds through the FCT-Portuguese Foundation for Science and Technology [FCOMP - 01-0124-FEDER-037281] This work is funded (or part-funded) by the ERDF European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT-Portuguese Foundation for Science and Technology within project FCOMP - 01-0124-FEDER-037281. Taylor & francis inc Philadelphia Si",
year = "2015",
month = jan,
day = "1",
doi = "10.1080/03610918.2014.901353",
language = "English",
volume = "44",
pages = "2622--2635",
journal = "Communications In Statistics-Simulation And Computation",
issn = "0361-0918",
publisher = "Taylor & Francis",
number = "10",
}