In the previous chapter, we looked at using R for the estimation of linear models, the groundwork upon which most data analysis is built. However, what is one supposed to do if the relationship between two variables is not linear? For this, we must use nonlinear methods, a topic to which this chapter is devoted.
We will start with extensions to linear regression and then move on to nonparametric regression. In this chapter, we'll cover the following topics:
Polynomial regression
Spline regression
General regression framework
Point-wise regression
Kernel density regression
Local polynomial regression