Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. The basic principle is that local averaging or smoothing is performed with respect to a kernel function.

This book provides uninitiated readers with a feeling for the principles, applications, and analysis of kernel smoothers. This is facilita

chapter 1|9 pages


chapter 2|48 pages

Univariate kernel density estimation

chapter 3|32 pages

Bandwidth selection

chapter 4|24 pages

Multivariate kernel density estimation

chapter 5|32 pages

Kernel regression

chapter 6|47 pages

Selected extra topics