Exploratory tools for clustering multivariate data

Publication Type:Journal Article
Year of Publication:2007
Authors:Atkinson, A, Riani, M
Journal:Computational Statistics & Data Analysis
Volume:52
Pagination:272–285
Date Published:September
ISSN:01679473
Keywords:algorithms, cluster, data-exploration, it
Abstract:

The forward search provides a series of robust parameter estimates based on increasing numbers of observations. The resulting series of robust Mahalanobis distances is used to cluster multivariate normal data. The method depends on envelopes of the distribution of the test statistics in forward plots. These envelopes can be found by simulation; flexible polynomial approximations to the envelopes are given. New graphical tools provide methods not only of detecting clusters but also of determining their membership. Comparisons are made with mclust and k -means clustering.

URL:http://dx.doi.org/10.1016/j.csda.2006.12.034
DOI:10.1016/j.csda.2006.12.034
Scratchpads developed and conceived by (alphabetical): Ed Baker, Katherine Bouton Alice Heaton Dimitris Koureas, Laurence Livermore, Dave Roberts, Simon Rycroft, Ben Scott, Vince Smith