multicmp: Flexible Modeling of Multivariate Count Data via the Multivariate Conway-Maxwell-Poisson Distribution

A toolkit containing statistical analysis models motivated by multivariate forms of the Conway-Maxwell-Poisson (COM-Poisson) distribution for flexible modeling of multivariate count data, especially in the presence of data dispersion. Currently the package only supports bivariate data, via the bivariate COM-Poisson distribution described in Sellers et al. (2016) <doi:10.1016/j.jmva.2016.04.007>. Future development will extend the package to higher-dimensional data.

Version: 1.1
Imports: stats, numDeriv
Published: 2018-06-29
Author: Kimberly Sellers [aut], Darcy Steeg Morris [aut], Narayanaswamy Balakrishnan [aut], Diag Davenport [aut, cre]
Maintainer: Diag Davenport <diag.davenport at gmail.com>
BugReports: https://github.com/diagdavenport/multicmp/issues
License: GPL-3
URL: http://dx.doi.org/10.1016/j.jmva.2016.04.007
NeedsCompilation: no
CRAN checks: multicmp results

Downloads:

Reference manual: multicmp.pdf
Package source: multicmp_1.1.tar.gz
Windows binaries: r-prerelease: multicmp_1.1.zip, r-release: multicmp_1.1.zip, r-oldrel: multicmp_1.1.zip
macOS binaries: r-prerelease: multicmp_1.1.tgz, r-release: multicmp_1.1.tgz, r-oldrel: multicmp_1.1.tgz
Old sources: multicmp archive

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