Missingness Aware Gaussian Mixture Models

Parameter estimation and classification for Gaussian Mixture Models (GMMs) in the presence of missing data. This package uses an expectation conditional maximization algorithm to obtain maximum likelihood estimates for all model parameters and maximum a posteriori classifications of the input vectors. For additional details, please see McCaw ZR, Julienne H, Aschard H. "MGMM: an R package for fitting Gaussian Mixture Models on Incomplete Data." .


Reference manual

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0.3.1 by Zachary McCaw, 8 months ago

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

Authors: Zachary McCaw [aut, cre]

Documentation:   PDF Manual  

GPL-3 license

Imports cluster, methods, mvnfast, plyr, Rcpp, stats

Suggests knitr, rmarkdown

Linking to Rcpp, RcppArmadillo

See at CRAN