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.
Bessel,stats, mvtnorm, ghyp, numDeriv, mixture

Bessel,stats, mvtnorm, ghyp, numDeriv, mixture, e1071

Cristina Tortora, Ryan P. Browne, Brian C. Franczak, and Paul D. McNicholas.
Bessel,stats, mvtnorm, ghyp, numDeriv, mixture, e1071,cluster

Cristina Tortora, Aisha ElSherbiny, Ryan P. Browne, Brian C. Franczak,  and Paul D. McNicholas.

Bessel,stats, mvtnorm, ghyp, numDeriv, mixture, e1071,cluster,
methods

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 Amos Donald D. [ctb].
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'(Tortora et al. (2016)<arXiv:1403.2332v7>), mixture of  multiple scaled generalized hyperbolic distributions. The 'cMSGHD' (Tortora et al. (2016)<arXiv:1403.2332v7>) is a 'MSGHD' with convex contour plots. The 'MCGHD' (Tortora et al. (2016)<arXiv:1403.2332v7>), mixture of  coalesced generalized hyperbolic distributions is a new more flexible model.