Applying the Poisson model for generalized linear regression

Generalized linear models allow response variables that have error distribution models other than a normal distribution (Gaussian). In this recipe, we will demonstrate how to apply Poisson as a family object within glm with regard to count data.

Getting ready

The prerequisite for this task is to prepare the count data, with all the input data values as integers.

How to do it...

Perform the following steps to fit the generalized linear regression model with the Poisson model:

1. Load the warpbreaks data, and use head to view the first few lines:

       > data(warpbreaks)
       > head(warpbreaks)
       Output:
           breaks wool tension
        1   26     A      L
        2   30     A      L
        3   54     A      L
        4   25     A      L
        5   70     A      L
        6   52     A      L  

2. We apply Poisson as a family object for the independent variable, tension, and the dependent variable, breaks:

        > rs1...