Review by Peter Diggle
“Baddeley, Rubak, and Turner have written a uniquely comprehensive account of modern statistical methods for the analysis of spatial point pattern data, aimed firmly at users and, crucially, made accessible to users by explicit linkage of the methods to their own excellent R package, spatstat.
Essential reading for anyone who needs to analyze spatial point pattern data properly or to teach others how to do so.”
—Peter J. Diggle, Distinguished University Professor, CHICAS, Lancaster University Medical School, UK
Review by Noel Cressie
“Baddeley, Rubak, and Turner’s book on spatial point patterns is part of a revolution in statistics, and the reader is buoyantly swept along with it.
From data handling, to exploratory data analysis, to advanced analytic tools, we are treated to the best in data science, where open-source software in the R language is used to integrate science and data through statistical thinking.
This is an excellent book, founded on methodology derived from statistical models of spatial point patterns, but focusing on the practical needs of the applied scientist.”
—Noel Cressie, Distinguished Professor, National Institute for Applied Statistics Research Australia, University of Wollongong
Review by Roger Bivand
“Spatial Point Patterns: Methodology and Applications with R is a rich statistical feast.
It is by turns humorous, serious, occasionally rather direct, but never talks down to the reader, who is taken as having a well-motivated interest in spatial point patterns.
I would argue that applied statisticians not yet conscious of such an interest will also relish the book’s stated intention of bringing its topical treatments back into mainstream statistical practice.
Being able to try everything out in R, largely using the spatstat package is a clear advantage; this is coupled with numerous relevant example data sets.
While cherry picking is possible—the index is more than adequate—all readers are advised to read at least whole chapters, best complete parts of the book, because the information to be found there is part of a tightly woven fabric.
Much can be re-read several times with both profit and pleasure by statisticians and non-statistician practitioners.
Sustaining this level of attention to detail through a long book is a splendid achievement.”
—Roger Bivand, Professor of Geography, Norwegian School of Economics, and Author and Maintainer of Packages for Spatial Data Analysis, R Project
Review by Andrew Bevan
“The analysis of spatial point patterns and processes is an exploding field of applied research across many science and social science disciplines.
This is thanks in no small part to the development of open-licensed, well-documented, methodologically sophisticated software implementations.
For at least a decade, the authors of this book have been at the forefront of a statistical programming revolution.
However, with wider academic access to these point pattern-and-process methods, there has also come a pressing need for clearer guidance on good practice for applied researchers at all stages from graduate studies onward.
Expressed in an elegant and accessible style, with substantial references for those wanting directions into the more specialist literature, as well as an excellent set of reproducible, multi-disciplinary case studies, this book provides exactly what is needed.
It is highly likely to become a classic.”
—Andrew Bevan, Institute of Archaeology, University College London