Kernel Smoothing (Hardcover, Softcover Repri)

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.

General

Imprint:	Chapman & Hall/CRC
Country of origin:	United States
Series:	Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Release date:	December 1994
First published:	1995
Authors:	M. P. Wand • M.C. Jones
Dimensions:	229 x 152 x 19mm (L x W x T)
Format:	Hardcover
Pages:	224
Edition:	Softcover Repri
ISBN-13:	978-0-412-55270-0
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Promotions
LSN:	0-412-55270-1
Barcode:	9780412552700

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