MVSKmod: Matrix-Variate Skew Linear Regression Models

An implementation of the alternating expectation conditional maximization (AECM) 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:	2025-05-09
DOI:	10.32614/CRAN.package.MVSKmod
Author:	Samuel Soon [aut, cre], Dipankar Bandyopadhyay [aut], Qingyang Liu [aut]
Maintainer:	Samuel Soon <samksoon2 at gmail.com>
BugReports:	https://github.com/soonsk-vcu/MVSKmod/issues
License:	MIT + file LICENSE
URL:	https://github.com/soonsk-vcu/MVSKmod
NeedsCompilation:	no
Materials:	README
CRAN checks:	MVSKmod results

Documentation:

Reference manual:

MVSKmod.pdf

Downloads:

Package source:	MVSKmod_0.1.0.tar.gz
Windows binaries:	r-devel: MVSKmod_0.1.0.zip, r-release: MVSKmod_0.1.0.zip, r-oldrel: not available
macOS binaries:	r-release (arm64): MVSKmod_0.1.0.tgz, r-oldrel (arm64): MVSKmod_0.1.0.tgz, r-release (x86_64): MVSKmod_0.1.0.tgz, r-oldrel (x86_64): MVSKmod_0.1.0.tgz

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