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)
- GitHub
- https://vpnsctl.github.io/mixpoissonreg/
- File a bug report
- mixpoissonreg results
- mixpoissonreg.pdf
- Version1.0.0
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release03/10/2021
Documentation
- VignetteGlobal and local influence analysis with the *mixpoissonreg* package
- VignetteConfidence and prediction intervals with the mixpoissonreg package
- VignetteMaximum-likelihood estimation with the mixpoissonreg package
- Vignettemixpoissonreg in the tidyverse
- VignetteAnalyzing overdispersed count data with the mixpoissonreg package
- MaterialREADME
- MaterialNEWS
Team
Alexandre B. Simas
Wagner Barreto-Souza
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- Imports15 packages
- Suggests9 packages