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: |
0.1.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Bessel, clusterGeneration, DistributionUtils, matlib, maxLik, truncnorm, pracma, matrixcalc, purrr |
| Suggests: |
knitr, rmarkdown |
| Published: |
2026-06-04 |
| DOI: |
10.32614/CRAN.package.MVNGmod |
| 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:
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