Get Free Shipping on orders over $79
Smoothing Techniques : With Implementation in S - Wolfgang Härdle

Smoothing Techniques

With Implementation in S

By: Wolfgang Härdle

Hardcover | 5 December 1990

At a Glance

Hardcover


$169.00

or 4 interest-free payments of $42.25 with

 or 

Ships in 7 to 10 business days

The author has attempted to present a book that provides a non-technical introduction into the area of non-parametric density and regression function estimation. The application of these methods is discussed in terms of the S computing environment. Smoothing in high dimensions faces the problem of data sparseness. A principal feature of smoothing, the averaging of data points in a prescribed neighborhood, is not really practicable in dimensions greater than three if we have just one hundred data points. Additive models provide a way out of this dilemma; but, for their interactiveness and recursiveness, they require highly effective algorithms. For this purpose, the method of WARPing (Weighted Averaging using Rounded Points) is described in great detail.

Other Editions and Formats

Paperback

Published: 19th October 2011

More in Probability & Statistics

Implementing R for Statistics - Christophe  Chesneau

RRP $180.95

$165.75

Introduction to Medical Statistics : 4th edition - Martin Bland

RRP $72.55

$62.75

14%
OFF
Research Methods and Statistics in Psychology : 8th Edition - Hugh Coolican
Rationality : What It Is, Why It Seems Scarce, Why It Matters - Steven Pinker
Sampling Theory and Practice - Casey Murphy
Practical Statistics - Nancy Maxwell

$437.75

Foundations of Statistics - Everett Davies
Mathematical Statistics with Applications : 7th Edition - Dennis Wackerly
Statistics for The Behavioral Sciences : 10th Edition - Frederick J. Gravetter