Wolfgang Härdle

Smoothing Techniques

With Implementation in S

• Broschiertes Buch

Produktbeschreibung

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.

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Produktdetails

• Springer Series in Statistics
• Verlag: Springer / Springer New York / Springer, Berlin
• Artikelnr. des Verlages: 978-1-4612-8768-1
• Softcover reprint of the original 1st ed. 1991
• Seitenzahl: 276
• Erscheinungstermin: 19. Oktober 2011
• Englisch
• Abmessung: 235mm x 155mm x 16mm
• Gewicht: 422g
• ISBN-13: 9781461287681
• ISBN-10: 1461287685
• Artikelnr.: 36121315

Autorenporträt

The book is addressed to both the theoretical and applied statistician. It can be used as an undergraduate text.

Inhaltsangabe

I. Density Smoothing.- 1. The Histogram.- 2. Kernel Density Estimation.- 3. Further Density Estimators.- 4. Bandwidth Selection in Practice.- II. Regression Smoothing.- 5. Nonparametric Regression.- 6. Bandwidth Selection.- 7. Simultaneous Error Bars.- Tables.- Solutions.- List of Used S Commands.- Symbols and Notation.- References.