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'(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.

Getting started

Package details

AuthorCristina 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].
MaintainerCristina Tortora <grikris1@gmail.com>
LicenseGPL (>= 2)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the MixGHD package in your browser

Any scripts or data that you put into this service are public.

MixGHD documentation built on Aug. 22, 2019, 5:12 p.m.