Show simple item record

dc.contributor.authorJ. McLachlan, Geoffry
dc.contributor.authorNg, Shu-Kay
dc.contributor.authorBean, Richard
dc.date.accessioned2017-05-03T15:26:09Z
dc.date.available2017-05-03T15:26:09Z
dc.date.issued2006
dc.date.modified2010-07-16T06:09:54Z
dc.identifier.issn1026597X
dc.identifier.urihttp://hdl.handle.net/10072/32320
dc.description.abstractFinite mixture models are being increasingly used to model the distributions of a wide variety of random phenomena and to cluster data sets. In this paper, we focus on the use of normal mixture models to cluster data sets of continuous multivariate data. As normality based methods of estimation are not robust, we review the use of t component distributions. With the t mixture model-based approach, the normal distribution for each component in the mixture model is embedded in a wider class of elliptically symmetric distributions with an additional parameter called the degrees of freedom. The advantage of the t mixture model is that, although the number of outliers needed for breakdown is almost the same as with the normal mixture model, the outliers have to be much larger. We also consider the use of the t distribution for the robust clustering of high-dimensional data via mixtures of factor analyzers. The latter enable a mixture model to be fitted to data which have high dimension relative to the number of data points to be clustered.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherOesterreichische Statistische Gesellschaft
dc.publisher.placeAustria
dc.publisher.urihttp://www.statistik.tuwien.ac.at/oezstat/
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom157
dc.relation.ispartofpageto174
dc.relation.ispartofissue2/3
dc.relation.ispartofjournalAustrian Journal of Statistics
dc.relation.ispartofvolume35
dc.rights.retentionY
dc.subject.fieldofresearchStatistics
dc.subject.fieldofresearchcode0104
dc.titleRobust cluster analysis via mixture models
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.date.issued2006
gro.hasfulltextNo Full Text
gro.griffith.authorNg, Shu Kay Angus


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

  • Journal articles
    Contains articles published by Griffith authors in scholarly journals.

Show simple item record