Package: MVNGmod 0.1.0

Samuel Soon

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>.

Authors:Samuel Soon [aut, cre], Dipankar Bandyopadhyay [aut], Qingyang Liu [aut]

MVNGmod_0.1.0.tar.gz
MVNGmod_0.1.0.zip(r-4.7-any)MVNGmod_0.1.0.zip(r-4.6-any)MVNGmod_0.1.0.zip(r-4.5-any)
MVNGmod_0.1.0.tgz(r-4.6-any)MVNGmod_0.1.0.tgz(r-4.5-any)
MVNGmod_0.1.0.tar.gz(r-4.7-any)MVNGmod_0.1.0.tar.gz(r-4.6-any)
MVNGmod_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MVNGmod/json (API)

# Install 'MVNGmod' in R:
install.packages('MVNGmod', repos = c('https://soonsk-vcu.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/soonsk-vcu/mvngmod/issues

Datasets:

On CRAN:

Conda:

2.00 score 460 downloads 3 exports 104 dependencies

Last updated from:4cf9742b10. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK241
source / vignettesOK249
linux-releaseOK200
macos-releaseOK196
macos-oldrelOK145
windows-develOK99
windows-releaseOK80
windows-oldrelOK84
wasm-releaseOK162

Exports:MVNIGmodMVVGmodpredict

Dependencies:abindbackportsbase64encBesselbootbroombslibcachemcarcarDatacliclusterGenerationcolorspacecowplotcpp11DerivdigestDistributionUtilsdoBydplyrevaluatefarverfastmapfontawesomeforecastFormulafracdifffsgenericsggplot2gluegmpgtablehighrhtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclelme4lmtestmagrittrMASSmatlibMatrixMatrixModelsmaxLikmemoisemgcvmimeminqamiscToolsmodelrnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpracmapurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrglrlangrmarkdownRmpfrrstudioapiS7sandwichsassscalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDatetinytextruncnormurcautf8vctrsviridisLitewithrxfunxtableyamlzoo