ENGLISH

Kernel Smoothing

By M. P. Wand , M. C. Jones (auth.)

Book information

Publisher
Springer US
Year
1995
ISBN
9780412552700, 0412552701
DOI
10.1007/978-1-4899-4493-1
LCC
QA278 .W32 1995
Open Library ID
OL1132534M
Language
english
Format
DJVU
Filesize
1 MB (1299012 bytes)
Series
Monographs on Statistics and Applied Probability 60
Edition
1st ed
Pages
222\222
Library
Kolxo3
DPI
600
Scanned
yes
Time added
2009-07-20 03:45:11

Description

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. Kernal 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.

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