Spatio-Temporal Statistics with R: 1st Edition (Hardback) book cover

Spatio-Temporal Statistics with R

1st Edition

By Christopher K. Wikle, Andrew Zammit-Mangion, Noel Cressie

Chapman and Hall/CRC

380 pages | 75 Color Illus. | 14 B/W Illus.

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pub: 2019-02-18
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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.


"Spatio-Temporal Statistics with R is the perfect companion to the earlier title by the authors on Statistics for Spatio-Temporal Data. This newest book augments the reader’s skillset by showing how to implement a variety of methods to create spatio-temporal graphics and perform data analysis. By making a massive set of data and code available, this book encourages the reader to follow along on the computer while working through the chapters. In fact, a unique element of the authors’ approach is that they provide a solid review of existing software and complement that with a new software package so that no techniques fall through the cracks. I also particularly like the series of text boxes throughout the book that detail expert tips for computing and include technical comments for more advanced readers. It is this masterful blend of information that beginners and power users alike will find critical for enhancing their understanding of spatio-temporal statistics in practice. This book will be recommended reading for all of my future graduate students!"

Mevin B. Hooten, Professor, Colorado State University and U.S. Geological Survey

"This book is an excellent offering from some of the leading researchers and authors in the field of spatio-temporal statistics. The book will be especially useful for scientists and researchers seeking a hands-on approach to statistical modeling and analysis for spatio-temporal data. The text is organized beautifully and offers a pleasing blend of technical material and computer programs for implementing a variety of spatio-temporal models. What is especially attractive is the detail with which the computer programs have been explained and exemplified. The theoretical and more technical material are supplied as "Technical Tips" in conspicuous boxes that accompany the modeling and computing details. The book will be useful to methodologists and practitioners working on spatio-temporal analysis and will especially appeal to the broader scientific community who will enjoy the very accessible treatment of spatial-temporal modeling and computing in an open-source and highly accessible software environment."

Sudipto Banerjee, Professor and Chair, Department of Biostatistics, University of California Los Angeles

Table of Contents

Introduction to Spatio-Temporal Statistics

Exploring Spatio-Temporal Data

Spatio-Temporal Statistical Models

Descriptive Spatio-Temporal Statistical Models

Dynamic Spatio-Temporal Models

Evaluating Spatio-Temporal Statistical Models

Pergimus (Epilogue)


About the Authors

CHRISTOPHER K. WIKLE is Curators’ Distinguished Professor and Chair of the Department of Statistics at the University of Missouri, USA.

ANDREW ZAMMIT-MANGION is a Discovery Early Career Researcher Award (DECRA) Fellow and Senior Lecturer in the School of Mathematics and Applied Statistics at the University of Wollongong, Australia.

NOEL CRESSIE, FAA is Distinguished Professor in the School of Mathematics and Applied Statistics and Director of the Centre for Environmental Informatics at the University of Wollongong, Australia.

About the Series

Chapman & Hall/CRC The R Series

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General