MVSKmod: Matrix-Variate Skew Linear Regression Models

An implementation of the alternating expectation conditional maximization (AECM) 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>.

Getting started

Package details

AuthorSamuel Soon [aut, cre], Dipankar Bandyopadhyay [aut], Qingyang Liu [aut]
MaintainerSamuel Soon <samksoon2@gmail.com>
LicenseMIT + file LICENSE
Version0.1.0
URL https://github.com/soonsk-vcu/MVSKmod
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("MVSKmod")

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MVSKmod documentation built on June 8, 2025, 1:46 p.m.