Matrix-Variate Non-Gaussian Linear Regression Models R package MVNGmod version 0.1.1 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>. Software Depends: R (>= 3.5.0) Imports: Bessel, clusterGeneration, DistributionUtils, matlib, maxLik, truncnorm, pracma, matrixcalc, purrr Suggests: knitr, rmarkdown Samuel Soon <samksoon2@gmail.com> Comprehensive R Archive Network (CRAN) Samuel Soon [aut, cre], Dipankar Bandyopadhyay [aut], Qingyang Liu [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=MVNGmod/LICENSE) 2026-06-04 application/tgz https://CRAN.R-project.org/package=MVNGmod doi:10.32614/CRAN.package.MVNGmod