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) ) is the classical mixture of generalized hyperbolic distributions. The 'MGHFA' (Tortora et al. (2016) ) 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). The paper related to the software can be found at .


Reference manual

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2.3.5 by Cristina Tortora, 4 months ago

Browse source code at

Authors: 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].

Documentation:   PDF Manual  

GPL (>= 2) license

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

Depends on MASS

System requirements: GNU make

See at CRAN