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>.
Package details |
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Author | Samuel Soon [aut, cre], Dipankar Bandyopadhyay [aut], Qingyang Liu [aut] |
Maintainer | Samuel Soon <samksoon2@gmail.com> |
License | MIT + file LICENSE |
Version | 0.1.0 |
URL | https://github.com/soonsk-vcu/MVSKmod |
Package repository | View on CRAN |
Installation |
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