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'(Tortora et al. (2016) ), mixture of multiple scaled generalized hyperbolic distributions. The 'cMSGHD' (Tortora et al. (2016) ) is a 'MSGHD' with convex contour plots. The 'MCGHD' (Tortora et al. (2016) ), mixture of coalesced generalized hyperbolic distributions is a new more flexible model.


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2.3.2 by Cristina Tortora, 14 days 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