Addons for the 'mclust' Package
Cumulative distribution and quantiles of univariate model-based mixtur...
Model-based mixture density estimation for bounded data
Gaussian mixture-based estimation of entropy
Modal EM algorithm for Gaussian Mixtures
Modeling log-returns distribution via Gaussian Mixture Models
Latin Hypercube Sampling
Simple Monte Carlo Sampling
Default HDR level defining the GMM hull
Gaussian mixture-based hypervolume estimation of multivariate data
Approximate hypervolume for multivariate data
Approximate hypervolume for multivariate data
Internal mclustAddons functions
Addons for the mclust package
Model-based clustering for bounded data
Recover parameters in the original scale
Marginal parameters from fitted GMMs via mclust
Modal EM algorithm for Gaussian Mixtures fitted via mclust package
Plotting method for model-based mixture density estimation for bounded...
Plotting method for model-based clustering of bounded data
Plotting method for modal-clustering based on Gaussian Mixtures
Model-based mixture density estimation for bounded data
Model-based clustering estimation for bounded data
Range–power transformation
Risk measures from Gaussian mixtures modeling
Financial risk measures
Extend the functionality of the 'mclust' package for Gaussian finite mixture modeling by including: density estimation for data with bounded support (Scrucca, 2019 <doi:10.1002/bimj.201800174>); modal clustering using MEM (Modal EM) algorithm for Gaussian mixtures (Scrucca, 2021 <doi:10.1002/sam.11527>); entropy estimation via Gaussian mixture modeling (Robin & Scrucca, 2023 <doi:10.1016/j.csda.2022.107582>); Gaussian mixtures modeling of financial log-returns (Scrucca, 2024 <doi:10.3390/e26110907>).