Smoothing Techniques
Wolfgang Härdle · 2011
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About the book
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.
Book details
- Year
- 2011
- Language
- English
- Publisher
- Springer
- Editions
- 3
- Pages
- 262
- ISBN
- 9781461287681
Data source: Wikidata
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