Book
Our book Spatial Point Patterns: Methodology and Applications with R was published in December 2015.
The book explains the principles and practice of
analysing spatial point patterns.
It is tightly integrated with spatstat, and provides a detailed guide to
using spatstat, as well as many templates for analysis using spatstat.
Discount price
For a 20% discount on the book price, please order the book using our promotion code AJL01 at the publisher’s webpage.
Book website
Visit the companion website for free sample chapters, R code for producing figures and output in all chapters, etc.
About the book
The book describes modern statistical methodology and software for analysing spatial point patterns. It is aimed primarily at scientists, across a broad range of disciplines, who need to analyse their own point pattern data. It provides clear explanations and practical advice on powerful statistical methodology for researchers who are results-oriented, together with authoritative guidance about the validity and applicability of different methods. Case studies in the book, and online supplementary examples and code, make it easy for readers to begin analysing their own data.
The book is not biased toward any particular area of science. Consequently, it covers a wider range of techniques than other books on spatial point pattern analysis which focus on a particular domain (ecology, geography, biology etc). For example, the chapter on `Intensity’ covers not only those techniques that are appropriate in spatial epidemiology (e.g. nonparametric kernel estimation of point process intensity and relative risk) but also those which are popular in geoscience (e.g. parametric modelling of intensity as a function of covariates using logistic regression).
Our book explains the core principles of statistical methodology for spatial point patterns. `Methodology’ is more than just a collection of tools: it is a systematic, principled, coherent approach to analysing data. These principles guide the appropriate choice of tool for each situation, and guide the correct interpretation of the results of analysis. By explaining the core principles we also make the methodology more comprehensible.
The book covers advanced techniques, yet it is focused on application. The availability of powerful software makes it possible for us to offer up-to-date, advanced statistical methodology without the sophisticated mathematical derivations and without the computational nitty-gritty, jumping straight from the core principles to the applications.
In presenting “modern” statistical methodology we include many older established techniques. The ad hoc methods popular in the 1980’s (e.g. Ripley’s K-function and its simulation envelopes) still have their place, but now have to share the limelight with newer methods (e.g. parametric models, likelihood devices, estimating equations, model diagnostics) that are also much closer to mainstream statistical science. Many of these newer techniques have not yet been covered in any book. Rather than following the traditional structure of books on point process statistics, the book is structured around standard statistical concepts as much as possible. This is both a pedagogical decision (to make the book more easily comprehensible to people who are trained in basic statistical concepts) and a scientific goal (to bring spatial point process analysis closer to the statistical mainstream).
The proliferation of research in spatial statistics has also led to some errors, misconceptions and confusion in the literature. An example is the confusion over the statistical significance of simulation envelopes. We hope our book will draw attention to many such common errors and misunderstandings. Written by leading researchers with a formidable combination of expertise and experience, the book should serve as an authoritative source of correct information about statistical tools for spatial point patterns.