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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): mpem_0.1.0.tgz, 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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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