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 |
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 binaries: | r-release: mmtfa_0.1.tgz, r-oldrel: mmtfa_0.1.tgz |
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