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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 |
| Reference manual: | multicmp.pdf |
| Package source: | multicmp_1.1.tar.gz |
| Windows binaries: | r-devel: multicmp_1.1.zip, r-release: multicmp_1.1.zip, r-oldrel: multicmp_1.1.zip |
| macOS binaries: | r-release (arm64): multicmp_1.1.tgz, r-oldrel (arm64): multicmp_1.1.tgz, r-release (x86_64): multicmp_1.1.tgz, r-oldrel (x86_64): multicmp_1.1.tgz |
| Old sources: | multicmp archive |
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These binaries (installable software) and packages are in development.
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