Spatio-Temporal Statistics with R (Chapman & Hall/CRC: The R Series)

by Andrew Zammit-Mangion (Author), Christopher K. Wikle (Author), Noel Cressie (Author)

• New

  Illustrated
  2019

  $61.70

  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.

  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.