mixpoissonreg: Mixed Poisson Regression for Overdispersed Count Data

Fits mixed Poisson regression models (Poisson-Inverse Gaussian or Negative-Binomial) on data sets with response variables being count data. The models can have varying precision parameter, where a linear regression structure (through a link function) is assumed to hold on the precision parameter. The Expectation-Maximization algorithm for both these models (Poisson Inverse Gaussian and Negative Binomial) is an important contribution of this package. Another important feature of this package is the set of functions to perform global and local influence analysis. See Barreto-Souza and Simas (2016) <doi:10.1007/s11222-015-9601-6> for further details.

Version: 1.0.0
Imports: pbapply, Formula, Rfast, dplyr, gamlss.dist, generics, ggplot2, gridExtra, lmtest, magrittr, statmod, tibble, rlang, ggrepel, gamlss
Suggests: rmarkdown, knitr, devtools, bbreg, testthat, covr, tidyr, ggfortify, broom
Published: 2021-03-10
Author: Alexandre B. Simas ORCID iD [aut, cre], Wagner Barreto-Souza ORCID iD [aut]
Maintainer: Alexandre B. Simas <alexandre.impa at gmail.com>
BugReports: https://github.com/vpnsctl/mixpoissonreg/issues
License: GPL-2
URL: https://github.com/vpnsctl/mixpoissonreg/, https://vpnsctl.github.io/mixpoissonreg/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mixpoissonreg results

Downloads:

Reference manual: mixpoissonreg.pdf
Vignettes: Global and local influence analysis with the *mixpoissonreg* package
Confidence and prediction intervals with the mixpoissonreg package
Maximum-likelihood estimation with the mixpoissonreg package
mixpoissonreg in the tidyverse
Analyzing overdispersed count data with the mixpoissonreg package
Package source: mixpoissonreg_1.0.0.tar.gz
Windows binaries: r-devel: mixpoissonreg_1.0.0.zip, r-release: mixpoissonreg_1.0.0.zip, r-oldrel: mixpoissonreg_1.0.0.zip
macOS binaries: r-release: mixpoissonreg_1.0.0.tgz, r-oldrel: mixpoissonreg_1.0.0.tgz

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