MVNGmod: Matrix-Variate Non-Gaussian Linear Regression Models

An implementation of the expectation conditional maximization (ECM) algorithm for matrix-variate variance gamma (MVVG) and normal-inverse Gaussian (MVNIG) linear models. These models are designed for settings of multivariate analysis with clustered non-uniform observations and correlated responses. The package includes fitting and prediction functions for both models, and an example dataset from a periodontal on Gullah-speaking African Americans, with responses in 'gaad_res', and covariates in 'gaad_cov'. For more details on the matrix-variate distributions used, see Gallaugher & McNicholas (2019) <doi:10.1016/j.spl.2018.08.012>.

Version:	0.1.0
Depends:	R (≥ 3.5.0)
Imports:	Bessel, clusterGeneration, DistributionUtils, matlib, maxLik, truncnorm, pracma
Published:	2026-02-23
DOI:	10.32614/CRAN.package.MVNGmod (may not be active yet)
Author:	Samuel Soon [aut, cre], Dipankar Bandyopadhyay [aut], Qingyang Liu [aut]
Maintainer:	Samuel Soon <samksoon2 at gmail.com>
BugReports:	https://github.com/soonsk-vcu/MVNGmod/issues
License:	MIT + file LICENSE
URL:	https://github.com/soonsk-vcu/MVNGmod
NeedsCompilation:	no
Materials:	README
CRAN checks:	MVNGmod results

Documentation:

Reference manual:

MVNGmod.html , MVNGmod.pdf

Downloads:

Package source:	MVNGmod_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): not available, r-oldrel (x86_64): not available

Linking:

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