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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

This project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.