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multicmp  

Flexible Modeling of Multivariate Count Data via the Multivariate Conway-Maxwell-Poisson Distribution
View on CRAN: Click here


Download and install multicmp package within the R console
Install from CRAN:
install.packages("multicmp")

Install from Github:
library("remotes")
install_github("cran/multicmp")

Install by package version:
library("remotes")
install_version("multicmp", "1.1")



Attach the package and use:
library("multicmp")
Maintained by
Diag Davenport
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-05-22
Latest Update: 2018-06-29
Description:
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) . Future development will extend the package to higher-dimensional data.
How to cite:
Diag Davenport (2017). multicmp: Flexible Modeling of Multivariate Count Data via the Multivariate Conway-Maxwell-Poisson Distribution. R package version 1.1, https://cran.r-project.org/web/packages/multicmp. Accessed 26 Oct. 2026.
Previous versions and publish date:
(2026-10-12 14:07), 1.0 (2017-05-22 06:17), 1.1 (2018-06-29 14:09)
Other packages that cited multicmp R package
View multicmp citation profile
Other R packages that multicmp depends, imports, suggests or enhances
Complete documentation for multicmp
Functions, R codes and Examples using the multicmp R package
Some associated functions: accidents . dbivCMP . multicmpests . 
Some associated R codes: data.R . multicmpests.R .  Full multicmp package functions and examples
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