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Geostatistical Functional Data Analysis.
・ISBN 978-1-119-38784-8 2021 hard US$ 136.95
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電子版あり 大学・学術機関向け電子ブック（eBook）ISBN 978-1-119-38791-6
| 著者・編者 | Mateu Mahiques, Jorge / Giraldo, Ramon, |
|---|---|
| シリーズ | Wiley Series in Probability and Statistics |
| 出版社 | (Wiley, US) |
| 出版年月 | 2021.10 |
| ページ数 | 300 pp. |
| 言語 | ENG |
| ニュース番号 | ＜662-L663 662-P1056＞ |
解説
Explore the intersection between geostatistics and functional data analysis with this insightful new reference
Geostatistical Functional Data Analysis presents a unified approach to modelling functional data when spatial and spatio-temporal correlations are present. The Editors link together the wide research areas of geostatistics and functional data analysis to provide the reader with a new area called geostatistical functional data analysis that will bring new insights and new open questions to researchers coming from both scientific fields. This book provides a complete and up-to-date account to deal with functional data that is spatially correlated, but also includes the most innovative developments in different open avenues in this field.
Containing contributions from leading experts in the field, this practical guide provides readers with the necessary tools to employ and adapt classic statistical techniques to handle spatial regression. The book also includes:
- A thorough introduction to the spatial kriging methodology when working with functions
- A detailed exposition of more classical statistical techniques adapted to the functional case and extended to handle spatial correlations
- Practical discussions of ANOVA, regression, and clustering methods to explore spatial correlation in a collection of curves sampled in a region
- In-depth explorations of the similarities and differences between spatio-temporal data analysis and functional data analysis
Aimed at mathematicians, statisticians, postgraduate students, and researchers involved in the analysis of functional and spatial data, Geostatistical Functional Data Analysis will also prove to be a powerful addition to the libraries of geoscientists, environmental scientists, and economists seeking insightful new knowledge and questions at the interface of geostatistics and functional data analysis.