mpem: Matrix Partial EM for Incomplete Matrix-Normal Data

Fits single-component and finite-mixture Kronecker-structured matrix-normal models and imputes incomplete matrix-variate data using matrix partial expectation-maximization. General MPEM handles arbitrary missingness, while Rect-MPEM exploits rectangular structural missingness. The methods are described in Lu, Andrews and Browne (2026) "An Efficient EM Algorithm for Both Element-Wise and Structural Missingness in Matrix-Variate Normal Mixture Models" <doi:10.48550/arXiv.2609.00616>.

Version: 0.1.0
Depends: R (≥ 4.1.0)
Imports: Rcpp, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (≥ 3.0.0)
Published: 2026-09-18
DOI: 10.32614/CRAN.package.mpem (may not be active yet)
Author: Hanzhang Lu [aut, cre, cph], Jeffrey L. Andrews [aut, ths], Ryan P. Browne [aut]
Maintainer: Hanzhang Lu <hanzhang.lu at ubc.ca>
BugReports: https://github.com/LHZMix/MPEM/issues
License: MIT + file LICENSE
URL: https://github.com/LHZMix/MPEM
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: mpem results

Documentation:

Reference manual: mpem.html , mpem.pdf

Downloads:

Package source: mpem_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): mpem_0.1.0.tgz, r-oldrel (x86_64): mpem_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mpem to link to this page.