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Spatio-Temporal Statistics with R. Rを用いた時空間統計学
・ISBN 978-1-138-71113-6 hard GB£ 67.99
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| 著者・編者 | Wikle, Christopher K. / Zammit-Mangion, A. / Cressie, N., |
|---|---|
| シリーズ | Chapman & Hall/CRC The R Series |
| 出版社 | (Chapman & Hall / CRC, US) |
| 出版年月 | 2019 |
| ページ数 | 396 pp. |
| 言語 | ENG |
| ニュース番号 | <648-412 648-P823> |
解説
The world is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps.
Spatio-Temporal Statistics with R provides an accessible introduction to statistical analysis of spatio-temporal data, with hands-on applications of the statistical methods using R Labs found at the end of each chapter. The book:
- Gives a step-by-step approach to analyzing spatio-temporal data, starting with visualization, then statistical modelling, with an emphasis on hierarchical statistical models and basis function expansions, and finishing with model evaluation
- Provides a gradual entry to the methodological aspects of spatio-temporal statistics
- Provides broad coverage of using R as well as "R Tips" throughout.
- Features detailed examples and applications in end-of-chapter Labs
- Features "Technical Notes" throughout to provide additional technical detail where relevant
- Supplemented by a website featuring the associated R package, data, reviews, errata, a discussion forum, and more
The book fills a void in the literature and available software, providing a bridge for students and researchers alike who wish to learn the basics of spatio-temporal statistics. It is written in an informal style and functions as a down-to-earth introduction to the subject. Any reader familiar with calculus-based probability and statistics, and who is comfortable with basic matrix-algebra representations of statistical models, would find this book easy to follow. The goal is to give as many people as possible the tools and confidence to analyze spatio-temporal data.