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mclust 5: Clustering, Classi?cation and Density Estimation Using Gaussian Finite Mixture Models.

Authors :
Scrucca, Luca
Fop, Michael
Murphy, T. Brendan
Raftery, Adrian E.
Source :
R Journal. Aug2016, Vol. 8 Issue 1, p289-317. 29p.
Publication Year :
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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20734859
Volume :
8
Issue :
1
Database :
Academic Search Index
Journal :
R Journal
Publication Type :
Academic Journal
Accession number :
118430367
Full Text :
https://doi.org/10.32614/RJ-2016-021