PUGMM

Parsimonious Ultrametric Gaussian Mixture Models

Parsimonious Ultrametric Gaussian Mixture Models via grouped coordinate ascent (equivalent to EM) algorithm characterized by the inspection of hierarchical relationships among variables via parsimonious extended ultrametric covariance structures. The methodologies are described in Cavicchia, Vichi, Zaccaria (2024) , (2022) and (2020) .

Reference manual

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install.packages("PUGMM")

0.1.2 by Giorgia Zaccaria, a year ago

https://github.com/giorgiazaccaria/PUGMM

Report a bug at https://github.com/giorgiazaccaria/PUGMM/issues

Browse source code at https://github.com/cran/PUGMM

Authors: Giorgia Zaccaria [aut, cre] (ORCID: , Carlo Cavicchia [aut] , Lorenzo Balzotti [aut] , Alexa A. Sochaniwsky [aut] (ORCID: , Paul D. McNicholas [aut] (ORCID:

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports ClusterR, doParallel, foreach, igraph, ManlyMix, MASS, Matrix, mclust, mcompanion, ppclust, Rcpp

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