Smoothing of multivariate data : density estimation and visualization /
An applied treatment of the key methods and state-of-the-art tools for visualizing and understanding statistical data. Smoothing of Multivariate Data provides an illustrative and hands-on approach to the multivariate aspects of density estimation, emphasizing the use of visualization tools. Rather t...
| Main Author: | |
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| Format: | eBook |
| Language: | English |
| Published: |
Hoboken, N.J. :
John Wiley & Sons,
[2009]
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| Series: | Wiley Online Library.
Wiley series in probability and statistics. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | An applied treatment of the key methods and state-of-the-art tools for visualizing and understanding statistical data. Smoothing of Multivariate Data provides an illustrative and hands-on approach to the multivariate aspects of density estimation, emphasizing the use of visualization tools. Rather than outlining the theoretical concepts of classification and regression, this book focuses on the procedures for estimating a multivariate distribution via smoothing. The author first provides an introduction to various visualization tools that can be used to construct representations of multivariate functions, sets, data, and scales of multivariate density estimates. Next, readers are presented with an extensive review of the basic mathematical tools that are needed to asymptotically analyze the behavior of multivariate density estimators, with coverage of density classes, lower bounds, empirical processes, and manipulation of density estimates. The book concludes with an extensive toolbox of multivariate density estimators, including anisotropic kernel estimators, minimization estimators, multivariate adaptive histograms, and wavelet estimators. |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (xxvi, 603 pages) : illustrations |
| Bibliography: | Includes bibliographical references (pages 575-590) and indexes. |
| ISBN: | 0470425660 (ebook) 0470425679 (ebook) 9780470425664 (ebook) 9780470425671 (ebook) |
| DOI: | 10.1002/9780470425671 |