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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>.

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 MVNGmod_0.1.0.tar.gz 143.0 KiB
0.1.0 rolling linux/noble R-4.5 MVNGmod_0.1.0.tar.gz 143.1 KiB
0.1.0 rolling source/ R- MVNGmod_0.1.0.tar.gz 73.5 KiB
0.1.0 latest linux/jammy R-4.5 MVNGmod_0.1.0.tar.gz 143.0 KiB
0.1.0 latest linux/noble R-4.5 MVNGmod_0.1.0.tar.gz 143.1 KiB
0.1.0 latest source/ R- MVNGmod_0.1.0.tar.gz 73.5 KiB
0.1.0 2026-04-26 source/ R- MVNGmod_0.1.0.tar.gz 73.5 KiB
0.1.0 2026-04-23 source/ R- MVNGmod_0.1.0.tar.gz 73.5 KiB
0.1.0 2026-04-09 windows/windows R-4.5 MVNGmod_0.1.0.zip 146.3 KiB

Dependencies (latest)

Imports