Model Wrappers for Poisson Regression

Bindings for Poisson regression models for use with the 'parsnip' package. Models include simple generalized linear models, Bayesian models, and zero-inflated Poisson models (Zeileis, Kleiber, and Jackman (2008) ).

poissonreg

poissonreg enables the parsnip package to fit various types of Poisson regression models including ordinary generalized linear models, simple Bayesian models (via rstanarm), and two zero-inflated Poisson models (via pscl).

Installation

You can install the released version of poissonreg from CRAN with:

install.packages("poissonreg")

Install the development version from GitHub with:

# install.packages("pak")
pak::pak("tidymodels/poissonreg")

Available Engines

The poissonreg package provides engines for the models in the following table.

model	engine	mode
poisson_reg	glm	regression
poisson_reg	hurdle	regression
poisson_reg	zeroinfl	regression
poisson_reg	glmnet	regression
poisson_reg	stan	regression

Example

A log-linear model for categorical data analysis:

library(poissonreg)

# 3D contingency table from Agresti (2007):
poisson_reg() |>
  set_engine("glm") |>
  fit(count ~ (.)^2, data = seniors)
#> parsnip model object
#> 
#> 
#> Call:  stats::glm(formula = count ~ (.)^2, family = stats::poisson, 
#>     data = data)
#> 
#> Coefficients:
#>               (Intercept)               marijuanayes  
#>                    5.6334                    -5.3090  
#>              cigaretteyes                 alcoholyes  
#>                   -1.8867                     0.4877  
#> marijuanayes:cigaretteyes    marijuanayes:alcoholyes  
#>                    2.8479                     2.9860  
#>   cigaretteyes:alcoholyes  
#>                    2.0545  
#> 
#> Degrees of Freedom: 7 Total (i.e. Null);  1 Residual
#> Null Deviance:       2851 
#> Residual Deviance: 0.374     AIC: 63.42

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