Smoothing Techniques : With Implementation in S PDF
by Wolfgang Hardle
Part of the Springer Series in Statistics series
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.
Information
-
Download - Immediately Available
- Format:PDF
- Publisher:Springer New York
- Publication Date:06/12/2012
- Category:
- ISBN:9781461244325
Information
-
Download - Immediately Available
- Format:PDF
- Publisher:Springer New York
- Publication Date:06/12/2012
- Category:
- ISBN:9781461244325
