Package: multicmp 1.0

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.

Authors:Kimberly Sellers [aut], Darcy Steeg Morris [aut], Narayanaswamy Balakrishnan [aut], Diag Davenport [aut, cre]

multicmp_1.0.tar.gz
multicmp_1.0.zip(r-4.7)multicmp_1.0.zip(r-4.6)multicmp_1.0.zip(r-4.5)
multicmp_1.0.tgz(r-4.6-any)multicmp_1.0.tgz(r-4.5-any)
multicmp_1.0.tar.gz(r-4.7-any)multicmp_1.0.tar.gz(r-4.6-any)
multicmp_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
multicmp/json (API)

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

Bug tracker:https://github.com/diagdavenport/multicmp/issues

Datasets:

On CRAN:

Conda:

2.00 score 4 scripts 149 downloads 2 exports 1 dependencies

Last updated from:b5e7d69340. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE96
source / vignettesOK124
linux-release-x86_64NOTE102
macos-release-arm64NOTE133
macos-oldrel-arm64NOTE172
windows-develNOTE100
windows-releaseNOTE77
windows-oldrelNOTE53
wasm-releaseOK112

Exports:dbivCMPmulticmpests

Dependencies:numDeriv