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).
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")
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 regressionA 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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