poissonreg-package: parsnip methods for Poisson regression

In poissonreg: Model Wrappers for Poisson Regression

parsnip methods for Poisson regression

Description

poissonreg offers a function to fit model to count data using Poisson generalized linear models or via different methods for zero-inflated Poisson (ZIP) models.

Details

The model function works with the tidymodels infrastructure so that the model can be resampled, tuned, tided, etc.

Example

Let’s fit a model to the data from Agresti (2007) Table 7.6:

library(poissonreg)
library(tidymodels)
tidymodels_prefer()

log_lin_fit <-
  # Define the model
  poisson_reg() %>%
  # Choose an engine for fitting. The default is 'glm' so
  # this next line is not strictly needed:
  set_engine("glm") %>%
  # Fit the model to the data:
  fit(count ~ (.)^2, data = seniors)

log_lin_fit

## 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

The different engines for the model that are provided by this package are:

show_engines("poisson_reg")

## # A tibble: 5 × 2
##   engine   mode      
##   <chr>    <chr>     
## 1 glm      regression
## 2 hurdle   regression
## 3 zeroinfl regression
## 4 glmnet   regression
## 5 stan     regression

Author(s)

Maintainer: Hannah Frick [e-mail] (ORCID)

Authors:

• Max Kuhn [e-mail] (ORCID)

Other contributors:

• RStudio [copyright holder, funder]

See Also

Useful links:

• https://github.com/tidymodels/poissonreg

• https://poissonreg.tidymodels.org/

• Report bugs at https://github.com/tidymodels/poissonreg/issues

poissonreg documentation built on Aug. 22, 2022, 5:07 p.m.