The roughness penalty approach

Abstract

In this chapter we introduce a third option for approximating discrete data by a function. The roughness penalty or regularization approach retains the advantages of the basis function and local expansion smoothing techniques developed in Chapter 3, but circumvents some of their limitations. More importantly, it adapts gracefully to more general functional data analysis problems that we consider in subsequent chapters.