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商品詳細
Wavelets in Functional Data Analysis. 1st ed. 2017.
・ISBN 978-3-319-59622-8 paper EUR 64.99
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お気に入り
★★★
| 著者・編者 | Morettin, Pedro A. / Pinheiro, Aluisio / Vidakovic, Brani, |
|---|---|
| シリーズ | SpringerBriefs in Mathematics |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2017 |
| ページ数 | 106 pp. |
| 言語 | ENG |
| ニュース番号 | <M25-7137> |
解説
Wavelet-based procedures are key in many areas of statistics, applied mathematics, engineering, and science. This book presents wavelets in functional data analysis, offering a glimpse of problems in which they can be applied, including tumor analysis, functional magnetic resonance and meteorological data. Starting with the Haar wavelet, the authors explore myriad families of wavelets and how they can be used. High-dimensional data visualization (using Andrews' plots), wavelet shrinkage (a simple, yet powerful, procedure for nonparametric models) and a selection of estimation and testing techniques (including a discussion on Stein's Paradox) make this a highly valuable resource for graduate students and experienced researchers alike.