mclustAddons-package {mclustAddons}R Documentation

Addons for the mclust package

Description

An R package extending the functionality of the mclust package (Scrucca et al. 2916, 2023) for Gaussian finite mixture modeling by including:

For a quick introduction to mclustAddons see the vignette A quick tour of mclustAddons.

Author(s)

Maintainer: Luca Scrucca luca.scrucca@unibo.it (ORCID) [copyright holder]

References

Scrucca L., Fop M., Murphy T. B. and Raftery A. E. (2016) mclust 5: clustering, classification and density estimation using Gaussian finite mixture models, The R Journal, 8/1, 205-233. doi:10.32614/RJ-2016-021

Scrucca L., Fraley C., Murphy T.B., Raftery A.E. (2023) Model-Based Clustering, Classification, and Density Estimation Using mclust in R. Chapman and Hall/CRC. doi:10.1201/9781003277965

Scrucca L. (2019) A transformation-based approach to Gaussian mixture density estimation for bounded data. Biometrical Journal, 61:4, 873–888. doi:10.1002/bimj.201800174

Scrucca L. (2021) A fast and efficient Modal EM algorithm for Gaussian mixtures. Statistical Analysis and Data Mining, 14:4, 305–314. doi:10.1002/sam.11527

Robin S. and Scrucca L. (2023) Mixture-based estimation of entropy. Computational Statistics & Data Analysis, 177, 107582. doi:10.1016/j.csda.2022.107582

See Also

densityMclustBounded() for density estimation of bounded data; MclustMEM() for modal clustering; EntropyGMM() for entropy estimation.


[Package mclustAddons version 0.9.1 Index]