Spatial data are collected in various ways, for example, weather maps, soil samples, incident patterns, microscopical slices, satellite, radar, or X-ray images. The statistical analysis of spatial data is treated as a separate topic, as it is different from classical statistical data in a number of ways. This book presents a concise introduction to the theory underlying the analysis of the main types of spatial data. It includes examples to illustrate the topics, including R code for their implementation, as well as exercises to support course teaching and self-study.
|Publisher:||Taylor & Francis|
|Series:||Chapman & Hall/CRC Texts in Statistical Science Series|
|Product dimensions:||6.12(w) x 9.25(h) x (d)|
About the Author
Marie-Colette van Lieshout is a Researcher in the group Stochastics of the Centre for Mathematics and Computer Science CWI and at the University Twente.
Table of Contents
Random field modelling and interpolation
Models and inference for areal unit data
Spatial point processes
Appendix: Solutions to theoretical exercises