dc.contributor.author | White, Arthur | en |
dc.date.accessioned | 2016-08-12T13:54:26Z | |
dc.date.available | 2016-08-12T13:54:26Z | |
dc.date.issued | 2016 | en |
dc.date.submitted | 2016 | en |
dc.identifier.citation | Arthur White and Thomas Brendan Murphy, Exponential family mixed membership models for soft?clustering of multivariate data, Advances in Data Analysis and Classification, 10, 4, 2016, 521-540 | en |
dc.identifier.other | Y | en |
dc.identifier.uri | http://hdl.handle.net/2262/76841 | |
dc.description | PUBLISHED | en |
dc.description.abstract | For several years, model-based clustering methods have successfully tackled many of the challenges presented by data-analysts. However, as the scope of data analysis has evolved, some problems may be beyond the standard mixture
model framework. One such problem is when observations in a dataset come from overlapping clusters, whereby different clusters will possess similar parameters for multiple variables. In this setting, mixed membership models, a soft clustering approach whereby observations are not restricted to single cluster membership, have proved to be an effective tool. In this paper, a method for fitting mixed membership models to data generated by a member of an exponential family is outlined. The method is applied to count data obtained from an ultra running competition, and compared with a standard mixture model approach. | en |
dc.description.sponsorship | This work is supported by Science Foundation Ireland under the Clique Strategic Research Cluster (08/SRC/I1407) and Insight Research Centre grant (SF1/12/RC/2289). | en |
dc.format.extent | 521-540 | en |
dc.language.iso | en | en |
dc.relation.ispartofseries | Advances in Data Analysis and Classification | en |
dc.relation.ispartofseries | 10 | en |
dc.relation.ispartofseries | 4 | en |
dc.rights | Y | en |
dc.subject | mixed membership models; model based clustering; variational Bayes. | en |
dc.title | Exponential family mixed membership models for soft?clustering of multivariate data | en |
dc.type | Journal Article | en |
dc.type.supercollection | scholarly_publications | en |
dc.type.supercollection | refereed_publications | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/arwhite | en |
dc.identifier.rssinternalid | 121957 | en |
dc.identifier.doi | https://dx.doi.org/10.1007/s11634-016-0267-5 | en |
dc.rights.ecaccessrights | openAccess | |
dc.subject.TCDTag | Applied Statistics | en |
dc.subject.TCDTag | BAYESIAN STATISTICS | en |
dc.subject.TCDTag | CLUSTERING | en |
dc.subject.TCDTag | Data Analysis | en |
dc.subject.TCDTag | METHODS, STATISTICAL | en |
dc.subject.TCDTag | MULTIVARIATE STATISTICS | en |
dc.subject.TCDTag | Mixed-membership models | en |
dc.subject.TCDTag | STATISTICAL ANALYSIS | en |
dc.subject.TCDTag | STATISTICAL-MODELS | en |
dc.subject.TCDTag | Statistical computing | en |
dc.subject.TCDTag | Statistics | en |
dc.subject.TCDTag | model based clustering | en |
dc.identifier.orcid_id | 0000-0002-7268-5163 | en |
dc.contributor.sponsor | SFI stipend | en |
dc.contributor.sponsorGrantNumber | 12/RC/2289 | en |
dc.contributor.sponsor | SFI stipend | en |
dc.contributor.sponsorGrantNumber | 08/SRC/I1407 | en |