Applying the Gaussian model for generalized linear regression

Generalized Linear Model (GLM) is a generalization of linear regression, which can include a link function to make a linear prediction. As a default setting, the family object for glm is Gaussian, which makes the glm function perform exactly the same as lm. In this recipe, we first demonstrate how to fit the model into the data using the glm function, and then show that glm with a Gaussian model performs exactly the same as lm.

Getting ready

Check whether the car library is installed and loaded as we require the SLID dataset from this package.

How to do it...

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

1. Fit the independent variables, age, sex, and education, and dependent variable wages to glm:

        > lmfit1 = glm(wages ~ age + sex + education, data = SLID, fami
        ly=gaussian)
        > summary(lmfit1)
        Output:

        Call:
        glm(formula = wages ~ age...