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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
The different engines for the model that are provided by this package are:
show_engines("poisson_reg")
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