mixture {mixture}R Documentation

Mixture Models for Clustering and Classification

Description

An implementation of 14 parsimonious clustering models for finite mixtures with components that are Gaussian, generalized hyperbolic, variance-gamma, Student's t, or skew-t, for model-based clustering and model-based classification, even with missing data.

Details

Package: mixture
Type: Package
Version: 2.1.2
Date: 2025-05-06
License: GPL (>=2)

This package contains the functions gpcm, tpcm, ghpcm, vgpcm, stpcm, e_step, ARI, and get_best_model, plus three simulated data sets.

This package also contains advanced functions for large system use which are: main_loop main_loop_vg , main_loop_gh, main_loop_t , main_loop_st ,z_ig_random_soft, z_ig_random_hard, z_ig_kmeans.

Author(s)

Nik Pocuca, Ryan P. Browne, Paul D. McNicholas, and Alexa A. Sochaniwsky.

Maintainer: Paul D. McNicholas <mcnicholas@math.mcmaster.ca>

See Also

Details, examples, and references are given under gpcm, tpcm, ghpcm, stpcm, and vgpcm.


[Package mixture version 2.1.2 Index]