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Smoothing Techniques: With Implementation in S (Springer Series in Statistics) - Softcover

 
9781461287681: Smoothing Techniques: With Implementation in S (Springer Series in Statistics)

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

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Härdle, Wolfgang
Published by Springer, 2011
ISBN 10: 1461287685 ISBN 13: 9781461287681
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Wolfgang Härdle
Published by Springer New York, 2011
ISBN 10: 1461287685 ISBN 13: 9781461287681
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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. Smoothin. Seller Inventory # 4191326

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Wolfgang Härdle
Published by Springer New York, 2011
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9781461287681

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Wolfgang Hardle
Published by Springer-Verlag New York Inc., 2011
ISBN 10: 1461287685 ISBN 13: 9781461287681
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Wolfgang Härdle
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch. Seller Inventory # 9781461287681

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Wolfgang H?rdle
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H?rdle Wolfgang
Published by Springer, 2011
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Condition: New. Print on Demand pp. 276 87 Figures, 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam. Seller Inventory # 51015089

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Published by Springer New York Okt 2011, 2011
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Taschenbuch. 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 # 9781461287681

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ISBN 10: 1461287685 ISBN 13: 9781461287681
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