Smoothing Techniques

With Implementation in S

By:

Wolfgang Hardle

Format:

Paperback / softback

Series:

Springer Series in Statistics

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Description

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.

Release date NZ

October 19th, 2011

Author

Wolfgang Hardle

Audience

Professional & Vocational

Edition

Softcover reprint of the original 1st ed. 1991

Illustrations

XII, 262 p.

Pages

262

Series

Springer Series in Statistics

Dimensions

156x234x14

ISBN-13

9781461287681

Product ID

20771965

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