Model Wrappers for Poisson Regression.
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:
require("devtools")
install_github("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
Contributing
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