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MVNGmod

Matrix-Variate Non-Gaussian Linear Regression Models

v0.1.1 · Jun 4, 2026 · MIT + file LICENSE

Description

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>.

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

OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 9, 2026
ERROR 12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Jun 8, 2026
ERROR r-devel-linux-x86_64-debian-gcc

package dependencies

Package required but not available: ‘matlib’

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies Bessel clusterGeneration DistributionUtils matlib maxLik truncnorm pracma matrixcalc purrr MVNGmod

Version History

2 tracked
updated 0.1.1 ← 0.1.0 diff Jun 4, 2026
new 0.1.0 Mar 10, 2026

R Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Feb 23, 2026. Releases before tracking aren’t shown.