MVNGmod: Matrix-Variate Non-Gaussian Linear Regression Models
Fits matrix-variate variance-gamma (MVVG) and matrix-variate normal-inverse-Gaussian (MVNIG) linear regression models using expectation-conditional maximization (ECM) algorithms. The models accommodate clustered matrix-valued responses, with unequal numbers of observations across subjects, correlated responses, skewness, and within-subject dependence. Functions are provided for model fitting, prediction, and subject-level influence assessment using approximate generalized Cook's distances. The package also includes motivating periodontal data from Gullah-speaking African Americans with Type-II diabetes. For details on the underlying matrix-variate distributions (MVVG and MVNIG), see Gallaugher and McNicholas (2019, <doi:10.1016/j.spl.2018.08.012>).
| Version: |
0.1.2 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Bessel, clusterGeneration, DistributionUtils, matlib, maxLik, truncnorm, pracma, matrixcalc, purrr |
| Suggests: |
knitr, rmarkdown |
| Published: |
2026-07-16 |
| 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 |
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