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Smoothing Techniques
Wolfgang H rdle
其他書名
With Implementation in S
出版Springer Science & Business Media, 1991
主題Gardening / GeneralMathematics / GeneralMathematics / AppliedMathematics / Probability & Statistics / General
ISBN03879736729780387973678
URLhttp://books.google.com.hk/books?id=2dzxO_zyRagC&hl=&source=gbs_api
EBookSAMPLE
註釋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.