Smoothing Techniques: With Implementation in S (Springer Series in Statistics) - Hardcover
Book 14 of 160: Springer Series in Statistics
Synopsis
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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Smoothing Techniques. With Implementation in S. Springer Series in Statistics
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Smoothing Techniques: With Implementation in S (Springer Series in Statistics)
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Smoothing Techniques. With Implementation in S.
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Hardcover. Condition: Sehr gut. N.Y., Springer (1991). gr.8°. XI, 261 p. Hardbound. (back faded, otherwise in very good condition).- With exercises. Seller Inventory # 94902
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Smoothing Techniques : With Implementation in S
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Smoothing Techniques: With Implementation in S (Springer Series in Statistics)
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Smoothing Techniques
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Springer New York Dez 1990, 1990
ISBN 10: 0387973672
ISBN 13: 9780387973678
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 276 pp. Englisch. Seller Inventory # 9780387973678
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Smoothing Techniques : With Implementation in S
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