Visualizing a generalized additive model

In this recipe, we demonstrate how to add a gam fitted regression line to a scatter plot. In addition, we visualize the gam fit using the plot function.

Getting ready

Complete the previous recipe by assigning a gam fitted model to the fit variable.

How to do it...

Perform the following steps to visualize the generalized additive model:

1. Generate a scatter plot using the nox and dis variables:

        > plot(nox, dis)  

Scatter plot of variable nox against dis

2. Add the regression to the scatter plot:

        > x = seq(0, 1, length = 500)
        > y = predict(fit, data.frame(nox = x))
        > lines(x, y, col = "red", lwd = 2) 

Fitted regression of gam on a scatter plot

3. Alternatively, you can plot the fitted model using the plot function:

        > plot(fit)  

Plot of fitted gam

How it works...

To visualize the fitted regression, we first generate a scatter plot using the dis and nox variables. Then, we generate the sequence of x-axis, and respond y...