Algorithms and methods for model-based clustering and classification.
It supports various types of data: continuous, categorical and counting
and can handle mixed data of these types. It can fit Gaussian (with diagonal
covariance structure), gamma, categorical and Poisson models. The algorithms
also support missing values. This package can be used as an independent
alternative to the (not free) 'mixtcomp' software available at
<https://massiccc.lille.inria.fr/>.

Model based clustering and classification using the mixture of
generalized hyperbolic distributions.
Cristina Tortora, Ryan P. Browne, Brian C. Franczak and Paul D. McNicholas.
Carries out model-based clustering using three different models. The models are all based on the  generalized hyperbolic distribution.The first model MGHD is the classical mixture of generalized hyperbolic distributions. The MGHFA is the mixture of generalized hyperbolic factor analyzers for high dimensional data sets. The MCGHD, mixture of  coalesced generalized hyperbolic distributions is a new more flexible model.
Bessel, stats, MASS, mvtnorm, ghyp, numDeriv, R (>= 3.1.1)

Model based clustering, classification and discriminant analysis
using the mixture of generalized hyperbolic distributions.
Carries out model-based clustering, classification and discriminant analysis using four different models. The models are all based on the  generalized hyperbolic distribution.The first model MGHD is the classical mixture of generalized hyperbolic distributions. The MGHFA is the mixture of generalized hyperbolic factor analyzers for high dimensional data sets. The MSGHD, mixture of  multiple scaled generalized hyperbolic distributions. The MCGHD, mixture of  coalesced generalized hyperbolic distributions is a new more flexible model.

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 is the classical mixture of generalized hyperbolic distributions. The MGHFA is the mixture of generalized hyperbolic factor analyzers for high dimensional data sets. The MSGHD, mixture of  multiple scaled generalized hyperbolic distributions. The cMSGHD is a MSGHD with convex contour plots. The MCGHD, mixture of  coalesced generalized hyperbolic distributions is a new more flexible model.