Rmixmod: TheRPackage of the Model-Based Unsupervised, Supervised, and Semi-Supervised ClassificationMixmodLibrary
Author(s) -
Rémi Lebret,
Serge Iovleff,
Florent Langrognet,
Christophe Biernacki,
Gilles Celeux,
Gérard Govaert
Publication year - 2015
Publication title -
journal of statistical software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.636
H-Index - 145
ISSN - 1548-7660
DOI - 10.18637/jss.v067.i06
Subject(s) - r package , cluster analysis , multinomial distribution , computer science , linear discriminant analysis , multivariate statistics , artificial intelligence , mixture model , pattern recognition (psychology) , software , gaussian , discriminant , multivariate normal distribution , software package , data mining , machine learning , mathematics , statistics , programming language , physics , computational science , quantum mechanics
Mixmod is a well-established software package for fitting mixture models of multivariate Gaussian or multinomial probability distribution functions to a given dataset with either a clustering, a density estimation or a discriminant analysis purpose. The Rmixmod S4 package provides an interface from the R statistical computing environment to the C++ core library of Mixmod (mixmodLib). In this article, we give an overview of the model-based clustering and classification methods implemented, and we show how the R package Rmixmod can be used for clustering and discriminant analysis.
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