Kernel Smoothing

1st Edition

M.P. Wand, M.C. Jones

Chapman and Hall/CRC
Published December 1, 1994
Reference - 224 Pages
ISBN 9780412552700 - CAT# C5270
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability

For Instructors Request Inspection Copy

USD$185.00

Add to Wish List
FREE Standard Shipping!

Summary

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 facilitated by the authors' focus on the simplest settings, namely density estimation and nonparametric regression. They pay particular attention to the problem of choosing the smoothing parameter of a kernel smoother, and also treat the multivariate case in detail.

Kernel Smoothing is self-contained and assumes only a basic knowledge of statistics, calculus, and matrix algebra. It is an invaluable introduction to the main ideas of kernel estimation for students and researchers from other discipline and provides a comprehensive reference for those familiar with the topic.

More information on the book, and the accompanying R package can be found here.

Instructors

We provide complimentary e-inspection copies of primary textbooks to instructors considering our books for course adoption.

Request an
e-inspection copy

Share this Title