mmtfa: Model-Based Clustering and Classification with Mixtures of Modified t Factor Analyzers

Fits a family of mixtures of multivariate t-distributions under a continuous t-distributed latent variable structure for the purpose of clustering or classification. The alternating expectation-conditional maximization algorithm is used for parameter estimation.

Version: 0.1
Imports: parallel, mvnfast, matrixStats
Published: 2015-06-14
Author: Jeffrey L. Andrews, Paul D. McNicholas, and Mathieu Chalifour
Maintainer: Jeffrey L. Andrews <jeffrey.andrews at macewan.ca>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: mmtfa results

Downloads:

Reference manual: mmtfa.pdf
Package source: mmtfa_0.1.tar.gz
Windows binaries: r-devel: mmtfa_0.1.zip, r-release: mmtfa_0.1.zip, r-oldrel: mmtfa_0.1.zip
OS X El Capitan binaries: r-release: mmtfa_0.1.tgz
OS X Mavericks binaries: r-oldrel: mmtfa_0.1.tgz

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