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mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models
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File | Description | Size | Format | |
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insight_publication.pdf | 769.47 KB |
Date Issued
01 August 2016
Date Available
15T13:53:47Z September 2016
Abstract
Finite mixture models are being used increasingly to model a wide variety of random phenomena for clustering, classification and density estimation. mclust is a powerful and popular package which allows modelling of data as a Gaussian finite mixture with different covariance structures and different numbers of mixture components, for a variety of purposes of analysis. Recently, version 5 of the package has been made available on CRAN. This updated version adds new covariance structures, dimension reduction capabilities for visualisation, model selection criteria, initialisation strategies for the EM algorithm, and bootstrap-based inference, making it a full-featured R package for data analysis via finite mixture modelling.
Sponsorship
Science Foundation Ireland
Type of Material
Journal Article
Publisher
R Foundation for Statistical Computing
Journal
The R Journal
Volume
8
Issue
1
Keywords
Web versions
Language
English
Status of Item
Peer reviewed
ISSN
2073-4859
This item is made available under a Creative Commons License
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