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MixGHD: Model Based Clustering, Classification and Discriminant Analysis Using the Mixture of Generalized Hyperbolic Distributions

Carries out model-based clustering, classification and discriminant analysis using five different models. The models are all based on the generalized hyperbolic distribution. The first model 'MGHD' (Browne and McNicholas (2015) <doi:10.1002/cjs.11246>) is the classical mixture of generalized hyperbolic distributions. The 'MGHFA' (Tortora et al. (2016) <doi:10.1007/s11634-015-0204-z>) is the mixture of generalized hyperbolic factor analyzers for high dimensional data sets. The 'MSGHD' is the mixture of multiple scaled generalized hyperbolic distributions, the 'cMSGHD' is a 'MSGHD' with convex contour plots and the 'MCGHD', mixture of coalesced generalized hyperbolic distributions is a new more flexible model (Tortora et al. (2019)<doi:10.1007/s00357-019-09319-3>. The paper related to the software can be found at <doi:10.18637/jss.v098.i03>.

Version: 2.3.7
Depends: MASS, R (≥ 3.1.3)
Imports: Bessel, stats, mvtnorm, ghyp, numDeriv, mixture, e1071, cluster, methods
Published: 2022-05-11
Author: Cristina Tortora [aut, cre, cph], Aisha ElSherbiny [com], Ryan P. Browne [aut, cph], Brian C. Franczak [aut, cph], and Paul D. McNicholas [aut, cph], and Donald D. Amos [ctb].
Maintainer: Cristina Tortora <grikris1 at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: MixGHD citation info
CRAN checks: MixGHD results

Documentation:

Reference manual: MixGHD.pdf

Downloads:

Package source: MixGHD_2.3.7.tar.gz
Windows binaries: r-devel: MixGHD_2.3.7.zip, r-release: MixGHD_2.3.7.zip, r-oldrel: MixGHD_2.3.7.zip
macOS binaries: r-release (arm64): MixGHD_2.3.7.tgz, r-oldrel (arm64): MixGHD_2.3.7.tgz, r-release (x86_64): MixGHD_2.3.7.tgz, r-oldrel (x86_64): MixGHD_2.3.7.tgz
Old sources: MixGHD archive

Reverse dependencies:

Reverse imports: vscc

Linking:

Please use the canonical form https://CRAN.R-project.org/package=MixGHD to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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