BASICS: Introduction. Software Essentials. Collecting and Handling Point Pattern Data. Inspecting and Exploring Data. Point Process Methods. EXPLORATORY DATA ANALYSIS: Intensity. Correlation. Spacing. STATISTICAL INFERENCE: Poisson Models. Hypothesis Tests and Simulation Envelopes. Model Validation. Cluster and Cox Models. Gibbs Models. Patterns of Several Types of Points. ADDITIONAL STRUCTURE: Higher-Dimensional Spaces and Marks. Replicated Point Patterns and Designed Experiments. Point Patterns on a Linear Network.
Adrian Baddeley is a professor of computational statistics at Curtin University and a fellow of the Australian Academy of Science. He has been a leading researcher in spatial statistics for 40 years.
Ege Rubak is an associate professor in the world-renowned spatial statistics group at Aalborg University. His research focuses on spatial statistics and statistical computing.
Rolf Turner is retired and an Honorary Research Fellow at the University of Auckland, where he has taught a graduate course on spatial point processes in the Department of Statistics. He has considerable expertise in statistical computing and has worked as a statistician in the Division of Mathematics and Statistics at CSIRO, the University of New Brunswick, and the Starpath Project at the University of Auckland.
"… A very broad range of topics is covered over 810 pages, using
examples from different fields of science, most notably astronomy,
biology, ecology, geology, and environmental sciences. In reading
the book, one of the most enjoyable features is the critical
attitude encouraged by the authors, who always question the
suitability of specific statistical methods in relation to a given
scientific question. The reader is guided from the first to the
last step of a statistical analysis of SPP data with useful advice
on modeling strategies and illustration of open-source statistical
software. The style is highly accessible to a nonstatistical
audience, with mathematical formalism kept to a minimum. … What
sets this book apart from others in its field are the strong link
that the authors build between statistical methodology and
scientific problems drawn from multidisciplinary case studies, the
coverage of a wide range of topics, and its reference to
highquality open-source statistical software. For these reasons,
the book is likely to become a classic in SPP data analysis."
—Emanuele Giorgi, Lancester University, in The American
Statistician, July 2017"The entire publication offers a wealth of
information and will serve as an excellent manual and guide for the
work of the point process statistician. One of the many strengths
of the book is that it consistently considers point process
statistics as a part of statistics in general and always to refer
to general statistical ideas. The text is very accessible…There are
a lot of interesting examples, which can be reproduced by the
reader in R. The reader will appreciate the frequent discussions of
caveats and the well-selected and well-answered FAQ’s (frequently
asked questions) at the end of each chapter…Overall, this
publication presents an excellent introduction to and manual for
the spatstat package, for which the community of spatial
statisticians will be very grateful to the authors. For readers who
use this software, it is an indispensable manual that the reviewer
strongly recommends…The reviewer is sure that it will initiate a
big step forward in the use of statistical methods for point
patterns."
—Dietrich Stoyan, TU Bergakademie Freiberg, Biometrical Journal,
January 2017"In a nutshell, this book covers a large portion of the
methods for the analysis of spatial point patterns and their
implementation in the spatstat package… As spatstat has evolved
with help from its users and the community, a list of frequently
asked questions (FAQ) is included at the end of most chapters. This
will help to clarify some of the contents and guide the user in the
data analysis by pointing at different important points to
consider. The book is also full of tips, clarifications and
discussions on how to conduct the analysis, which clearly will
benefit practitioners. It presents and discusses many applications
from different fields, so that it will be of interest to a wide
range of researchers…I really enjoyed reading this book and it has
changed my views on spatstat. In addition to a package for the
analysis of point patterns, I now regard this package as a toolbox
that will allow the development of further methods and software for
the analysis of point patterns, as the package provides a number of
functions to rely on when developing new methods."
—Virgilio Gómez-Rubio, Universidad de Castilla-La Mancha, Journal
of Statistical Software, December 2016"Several books on analysing
point pattern processes have been published in recent years; this
is by far the largest, at least in part due to the inclusion of
example scripts and output. Its central tool is the spatstat
package in R. Chapters cover spatial point pattern statistics from
first principles through to some of the more sophisticated
techniques. Its audience is scientists looking to employ and
interpret these tools, and while technical sections are included,
they expand on the applied material rather than being core. This
will prove a valuable reference and its guidance will improve
standards in the field."
—Markus Eichhorn, Frontiers of Biogeography, 2016, Volume 8, Issue
3"As the authors point out in their preface, the book is not
intended to be an introduction to point process theory for
mathematicians. Rather, they aim to focus on the principles of
statistical inference for spatial data and to help researchers in
application domains with the practicalities of the analysis and the
interpretation of the results. In this, they have succeeded
brilliantly...The book is written in a distinct, at times funny,
always accessible style. General principles of every aspect of
spatial point pattern analysis, from data collection to model
validation, are discussed in great detail with pointers to the
specialized literature for those who wish to gain a deeper
understanding of the technicalities. The principles are illustrated
by means of a wide collection of examples that can be reproduced by
the reader in R. Moreover, a selection of frequently asked
questions from spatstat users is answered at the end of each
chapter...In summary, I warmly recommend the book to anyone who
wishes to analyze point patterns professionally."
—Marie-Colette van Lieshout, reviewed in Biometrics, June
2016"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"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"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"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
"… A very broad range of topics is covered over 810 pages, using
examples from different fields of science, most notably astronomy,
biology, ecology, geology, and environmental sciences. In reading
the book, one of the most enjoyable features is the critical
attitude encouraged by the authors, who always question the
suitability of specific statistical methods in relation to a given
scientific question. The reader is guided from the first to the
last step of a statistical analysis of SPP data with useful advice
on modeling strategies and illustration of open-source statistical
software. The style is highly accessible to a nonstatistical
audience, with mathematical formalism kept to a minimum. … What
sets this book apart from others in its field are the strong link
that the authors build between statistical methodology and
scientific problems drawn from multidisciplinary case studies, the
coverage of a wide range of topics, and its reference to
highquality open-source statistical software. For these reasons,
the book is likely to become a classic in SPP data analysis."
—Emanuele Giorgi, Lancester University, in The American
Statistician, July 2017"The entire publication offers a wealth of
information and will serve as an excellent manual and guide for the
work of the point process statistician. One of the many strengths
of the book is that it consistently considers point process
statistics as a part of statistics in general and always to refer
to general statistical ideas. The text is very accessible…There are
a lot of interesting examples, which can be reproduced by the
reader in R. The reader will appreciate the frequent discussions of
caveats and the well-selected and well-answered FAQ’s (frequently
asked questions) at the end of each chapter…Overall, this
publication presents an excellent introduction to and manual for
the spatstat package, for which the community of spatial
statisticians will be very grateful to the authors. For readers who
use this software, it is an indispensable manual that the reviewer
strongly recommends…The reviewer is sure that it will initiate a
big step forward in the use of statistical methods for point
patterns."
—Dietrich Stoyan, TU Bergakademie Freiberg, Biometrical Journal,
January 2017"In a nutshell, this book covers a large portion of the
methods for the analysis of spatial point patterns and their
implementation in the spatstat package… As spatstat has evolved
with help from its users and the community, a list of frequently
asked questions (FAQ) is included at the end of most chapters. This
will help to clarify some of the contents and guide the user in the
data analysis by pointing at different important points to
consider. The book is also full of tips, clarifications and
discussions on how to conduct the analysis, which clearly will
benefit practitioners. It presents and discusses many applications
from different fields, so that it will be of interest to a wide
range of researchers…I really enjoyed reading this book and it has
changed my views on spatstat. In addition to a package for the
analysis of point patterns, I now regard this package as a toolbox
that will allow the development of further methods and software for
the analysis of point patterns, as the package provides a number of
functions to rely on when developing new methods."
—Virgilio Gómez-Rubio, Universidad de Castilla-La Mancha, Journal
of Statistical Software, December 2016"Several books on analysing
point pattern processes have been published in recent years; this
is by far the largest, at least in part due to the inclusion of
example scripts and output. Its central tool is the spatstat
package in R. Chapters cover spatial point pattern statistics from
first principles through to some of the more sophisticated
techniques. Its audience is scientists looking to employ and
interpret these tools, and while technical sections are included,
they expand on the applied material rather than being core. This
will prove a valuable reference and its guidance will improve
standards in the field."
—Markus Eichhorn, Frontiers of Biogeography, 2016, Volume 8, Issue
3"As the authors point out in their preface, the book is not
intended to be an introduction to point process theory for
mathematicians. Rather, they aim to focus on the principles of
statistical inference for spatial data and to help researchers in
application domains with the practicalities of the analysis and the
interpretation of the results. In this, they have succeeded
brilliantly...The book is written in a distinct, at times funny,
always accessible style. General principles of every aspect of
spatial point pattern analysis, from data collection to model
validation, are discussed in great detail with pointers to the
specialized literature for those who wish to gain a deeper
understanding of the technicalities. The principles are illustrated
by means of a wide collection of examples that can be reproduced by
the reader in R. Moreover, a selection of frequently asked
questions from spatstat users is answered at the end of each
chapter...In summary, I warmly recommend the book to anyone who
wishes to analyze point patterns professionally."
—Marie-Colette van Lieshout, reviewed in Biometrics, June
2016"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"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"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"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
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