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MGMM

Missingness-Aware Gaussian Mixture Models

v1.0.1.3 · Feb 26, 2026 · GPL-3

Description

Parameter estimation and classification for Gaussian Mixture Models (GMMs) in the presence of missing data. This package complements existing implementations by allowing for both missing elements in the input vectors and full (as opposed to strictly diagonal) covariance matrices. Estimation is performed using an expectation conditional maximization algorithm that accounts for missingness of both the cluster assignments and the vector components. The output includes the marginal cluster membership probabilities; the mean and covariance of each cluster; the posterior probabilities of cluster membership; and a completed version of the input data, with missing values imputed to their posterior expectations. For additional details, please see McCaw ZR, Julienne H, Aschard H. "Fitting Gaussian mixture models on incomplete data." <doi:10.1186/s12859-022-04740-9>.

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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-windows-x86_64 OK
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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Apr 22, 2026
ERROR 13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Apr 18, 2026
ERROR r-devel-windows-x86_64

whether package can be installed

Installation failed.
See 'd:/Rcompile/CRANpkg/local/4.6/MGMM.Rcheck/00install.out' for details.
OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies cluster glue mvnfast plyr Rcpp MGMM

Version History

7 tracked
new 1.0.1.3 Mar 10, 2026
updated 1.0.1.3 ← 1.0.1.1 diff Feb 25, 2026
updated 1.0.1.1 ← 1.0.1 diff Sep 29, 2023
updated 1.0.1 ← 1.0.0 diff Aug 7, 2023
updated 1.0.0 ← 0.4.0 diff Dec 20, 2021
updated 0.4.0 ← 0.3.1 diff Jul 24, 2021
new 0.3.1 Aug 25, 2020