Mean-Parametrized Conway-Maxwell Poisson (COM-Poisson) Regression

A collection of functions for estimation, testing and diagnostic checking for the mean-parametrized Conway-Maxwell Poisson (COM-Poisson) regression model of Huang (2017) .


The 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).

The mpcmp currently only supports log-lienar mean models, however work is progressing to incorporate regression being linked to the dispersion parameter and a zero-inflated Conway-Maxwell Poisson model.

Installation

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)

Usage

A reference manual is available at thomas-fung.github.io/mpcmp

Citation

If you use this package to analyse your data, please use the following citation:

  • Fung, T., Alwan, A., Wishart, J. and Huang, A. (2019). "The mpcmp package for Mean-parametrized Conway-Maxwell Poisson Regression."

From R you can use:

citation("mpcmp")
toBibtex(citation("mpcmp"))

News

Reference manual

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install.packages("mpcmp")

0.1.3 by Thomas Fung, 3 months ago


https://github.com/thomas-fung/mpcmp


Browse source code at https://github.com/cran/mpcmp


Authors: Thomas Fung [aut, cre] , Aya Alwan [aut] , Justin Wishart [aut] , Alan Huang [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports graphics, grDevices, stats

Suggests knitr, rmarkdown


See at CRAN