mpcmp: Mean-parametrized Conway-Maxwell Poisson Regression
mpcmp package provides a collection of functions for estimation, testing and diagnostic checking for the mean-parametrized Conway-Maxwell Poisson (COM-Poisson) regression model for under- and over-dispersed count data of Huang (2017).
From version 0.3.0,
mpcmp supports log-linear mean models, also allows one to incorporate regression being linked to the dispersion parameter.
Work is progressing to include a zero-inflated Conway-Maxwell-Poisson model.
Stable release on CRAN
The mpcmp package has been on CRAN since March 2019. You can install it from CRAN in the usual way:
Development version on Github
You can use the devtools package to install the development version of mpcmp from GitHub:
# install.packages("devtools") devtools::install_github("thomas-fung/mpcmp") library(mpcmp)
A reference manual and some examples are available at thomas-fung.github.io/mpcmp
If you use this package to analyse your data, please use the following citation:
- Fung, T., Alwan, A., Wishart, J. and Huang, A. (2021). mpcmp: Mean-parametrized Conway-Maxwell Poisson Regression. R package version 0.3.7.
From R you can use: