Our new book Spatio-Temporal Statistics with R has now been published with Chapman & Hall/CRC. It was a great few years writing this book with Chris Wikle and Noel Cressie, and I’m overjoyed to see the finished product. The book can be downloaded for free here. A hard-cover edition of the book can be purchased from Chapman & Hall/CRC here (Discount code: ASA18).
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.