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mvord: Multivariate Ordinal Regression Models

A flexible framework for fitting multivariate ordinal regression models with composite likelihood methods. Methodological details are given in Hirk, Hornik, Vana (2020) <doi:10.18637/jss.v093.i04>.

Version: 1.2.5
Depends: minqa, BB, ucminf, dfoptim, R (≥ 3.5.0)
Imports: MASS, pbivnorm, stats, optimx, mnormt, numDeriv, Matrix, mvtnorm
Suggests: knitr, rmarkdown, xtable, colorspace, LMest, VGAM
Published: 2024-08-30
DOI: 10.32614/CRAN.package.mvord
Author: Rainer Hirk [aut], Kurt Hornik ORCID iD [aut], Laura Vana ORCID iD [aut, cre], Alan Gentz [ctb]
Maintainer: Laura Vana <laura.vana at tuwien.ac.at>
BugReports: https://github.com/lauravana/mvord/issues
License: GPL-3
URL: https://github.com/lauravana/mvord
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: mvord results

Documentation:

Reference manual: mvord.pdf
Vignettes: mvord: Additional examples (source, R code)
mvord: An R Package for Fitting Multivariate Ordinal Regression Models (source, R code)

Downloads:

Package source: mvord_1.2.5.tar.gz
Windows binaries: r-devel: mvord_1.2.5.zip, r-release: mvord_1.2.5.zip, r-oldrel: mvord_1.2.5.zip
macOS binaries: r-release (arm64): mvord_1.2.5.tgz, r-oldrel (arm64): mvord_1.2.5.tgz, r-release (x86_64): mvord_1.2.5.tgz, r-oldrel (x86_64): mvord_1.2.5.tgz
Old sources: mvord archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.