mclustAddons-package | R Documentation |
Extend the functionality of the mclust package for Gaussian finite mixture modeling by including:
density estimation for data with bounded support (Scrucca, 2019)
modal clustering using MEM algorithm for Gaussian mixtures (Scrucca, 2021)
entropy estimation via Gaussian mixture modeling (Robin & Scrucca, 2023)
For a quick introduction to mclustAddons see the vignette A quick tour of mclustAddons.
See also:
densityMclustBounded()
for density estimation of bounded data;
MclustMEM()
for modal clustering;
EntropyGMM()
for entropy estimation.
Luca Scrucca.
Maintainer: Luca Scrucca luca.scrucca@unipg.it
Scrucca L. (2019) A transformation-based approach to Gaussian mixture density estimation for bounded data. Biometrical Journal, 61:4, 873–888. https://doi.org/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. https://doi.org/10.1002/sam.11527
Robin S. and Scrucca L. (2023) Mixture-based estimation of entropy. Computational Statistics & Data Analysis, 177, 107582. https://doi.org/10.1016/j.csda.2022.107582
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