pgmm: Parsimonious Gaussian Mixture Models

Carries out model-based clustering or classification using parsimonious Gaussian mixture models. McNicholas and Murphy (2008) <doi:10.1007/s11222-008-9056-0>, McNicholas (2010) <doi:10.1016/j.jspi.2009.11.006>, McNicholas and Murphy (2010) <doi:10.1093/bioinformatics/btq498>, McNicholas et al. (2010) <doi:10.1016/j.csda.2009.02.011>.

Version: 1.2.5
Published: 2021-11-03
Author: Paul D. McNicholas [aut, cre], Aisha ElSherbiny [aut], K. Raju Jampani [ctb], Aaron F. McDaid [aut], T. Brendan Murphy [aut], Larry Banks [ctb]
Maintainer: Paul D. McNicholas <mcnicholas at math.mcmaster.ca>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: ChangeLog
CRAN checks: pgmm results

Documentation:

Reference manual: pgmm.pdf

Downloads:

Package source: pgmm_1.2.5.tar.gz
Windows binaries: r-devel: pgmm_1.2.5.zip, r-release: pgmm_1.2.5.zip, r-oldrel: pgmm_1.2.5.zip
macOS binaries: r-release (arm64): pgmm_1.2.5.tgz, r-oldrel (arm64): pgmm_1.2.5.tgz, r-release (x86_64): pgmm_1.2.5.tgz, r-oldrel (x86_64): pgmm_1.2.5.tgz
Old sources: pgmm archive

Reverse dependencies:

Reverse imports: bpgmm

Linking:

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