Model-Based Clustering, Classification, and Discriminant Analysis Using the Generalized Hyperbolic Distribution: MixGHD R package

Model-Based Clustering, Classification, and Discriminant Analysis Using the Generalized Hyperbolic Distribution: MixGHD R package

model-based clustering, classification, discriminant analysis, EM algorithm, generalized hyperbolic distribution

The MixGHD package for R performs model-based clustering, classification, and discriminant analysis using the generalized hyperbolic distribution (GHD). This approach
is suitable for data that can be considered a realization of a (multivariate) continuous
random variable. The GHD has the advantage of being flexible due to skewness, concentration, and index parameters; as such, clustering methods that use this distribution are
capable of estimating clusters characterized by different shapes. The package provides
five different models all based on the GHD, an efficient routine for discriminant analysis,
and a function to measure cluster agreement. This paper is split into three parts: the
first is devoted to the formulation of each method, extending them for classification and
discriminant analysis applications, the second focuses on the algorithms, and the third
shows the use of the package on real datasets.

Cristina Tortora

https://www.jstatsoft.org/article/view/v098i03

MacEwan University

May 2021

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