Spatial point processes play a fundamental role in spatial statistics and today they are an active area of research with many new applications. Although other published works address different aspects of spatial point processes, most of the classical literature deals only with nonparametric methods, and a thorough treatment of the theory and applications of simulation-based inference is difficult to find. Written by researchers at the top of the field, this book collects and unifies recent theoretical advances and examples of applications. The authors examine Markov chain Monte Carlo algorithms and explore one of the most important recent developments in MCMC: perfect simulation procedures.

Point process statistics is successfully used in fields such as material science, human epidemiology, social sciences, animal epidemiology, biology, and seismology. Its further application depends greatly on good software and instructive case studies that show the way to successful work. This book satisfies this need by a presentation of the spatstat package and many statistical examples. Researchers, spatial statisticians and scientists from biology, geosciences, materials sciences and other fields will use this book as a helpful guide to the application of point process statistics. No other book presents so many well-founded point process case studies. From the reviews: "For those interested in analyzing their spatial data, the wide variatey of examples and approaches here give a good idea of the possibilities and suggest reasonable paths to explore." Michael Sherman for the Journal of the American Statistical Association, December 2006

Methoden zur Konstruktion von Risikozonen, die verwendet werden können, wenn ein räumliches Punktmuster unvollständig beobachtet wurde, werden am Beispiel von Blindgängern auf Bundesliegenschaften in Deutschland eingeführt und evaluiert. Blindgänger aus dem Zweiten Weltkrieg stellen in Deutschland ein schwerwiegendes Problem dar. Es ist daher wünschenswert, Risikozonen nach Blindgängern abzusuchen. Da dies jedoch hohe Kosten verursacht, beschränkt sich die Suche normalerweise auf sorgfältig ausgewählte Gebiete. Falls für das fragliche Gebiet geeignete Luftbilder existieren, können zur Bestimmung solcher Zonen statistische Methoden angewandt werden, indem das Muster der detonierten Bomben als Realisation eines räumlichen Punktprozesses betrachtet wird. Die in dieser Arbeit analysierten Muster wurden von der Oberfinanzdirektion Niedersachsen zur Verfügung gestellt, die die Kampfmittelräumung auf deutschen Bundesliegenschaften unterstützt. Sie wurden aus Luftbildern gewonnen, die die Alliierten während und nach dem Zweiten Weltkrieg aufgenommen haben. Das primäre Ziel besteht darin, möglichst kleine Regionen zu finden, die möglichst viele Blindgänger enthalten. Methods for constructing high-risk zones, which can be used in situations where a spatial point pattern has been observed incompletely, are introduced and evaluated with regard to unexploded bombs in federal properties in Germany. Unexploded bombs from the Second World War represent a serious problem in Germany. It is desirable to search high-risk zones for unexploded bombs, but this causes high costs, so the search is usually restricted to carefully selected areas. If suitable aerial pictures of the area in question exist, statistical methods can be used to determine such zones by considering patterns of exploded bombs as realisations of spatial point processes. The patterns analysed in this thesis were provided by Oberfinanzdirektion Niedersachsen, which supports the removal of unexploded ordnance in federal properties in Germany. They were derived from aerial pictures taken by the Allies during and after World War II. The main task consists of finding as small regions as possible containing as many unexploded bombs as possible.

Spatial point processes are mathematical models used to describe and analyse the geometrical structure of patterns formed by objects that are irregularly or randomly distributed in one-, two- or three-dimensional space. Examples include locations of trees in a forest, blood particles on a glass plate, galaxies in the universe, and particle centres in samples of material. Numerous aspects of the nature of a specific spatial point pattern may be described using the appropriate statistical methods. Statistical Analysis and Modelling of Spatial Point Patterns provides a practical guide to the use of these specialised methods. The application-oriented approach helps demonstrate the benefits of this increasingly popular branch of statistics to a broad audience. The book: Provides an introduction to spatial point patterns for researchers across numerous areas of application Adopts an extremely accessible style, allowing the non-statistician complete understanding Describes the process of extracting knowledge from the data, emphasising the marked point process Demonstrates the analysis of complex datasets, using applied examples from areas including biology, forestry, and materials science Features a supplementary website containing example datasets. Statistical Analysis and Modelling of Spatial Point Patterns is ideally suited for researchers in the many areas of application, including environmental statistics, ecology, physics, materials science, geostatistics, and biology. It is also suitable for students of statistics, mathematics, computer science, biology and geoinformatics.

Este libro de proceedings se edita para ponerlo a disposición de los asistentes a la Internacional Conference on Spatial Pont Process Modelling and its Applications (SPPA), realizada en Benicàssim en abril de 2004.

Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area. It takes a unified, integrated approach to the material, providing cross-references among chapters.The handbook begins with a historical intro

This volume provides a modern introduction to stochastic geometry, random fields and spatial statistics at a (post)graduate level. It is focused on asymptotic methods in geometric probability including weak and strong limit theorems for random spatial structures (point processes, sets, graphs, fields) with applications to statistics. Written as a contributed volume of lecture notes, it will be useful not only for students but also for lecturers and researchers interested in geometric probability and related subjects.

This volume offers a unique and accessible overview of the most active fields in Stochastic Geometry, up to the frontiers of recent research. Since 2014, the yearly meeting of the French research structure GDR GeoSto has been preceded by two introductory courses. This book contains five of these introductory lectures. The first chapter is a historically motivated introduction to Stochastic Geometry which relates four classical problems (the Buffon needle problem, the Bertrand paradox, the Sylvester four-point problem and the bicycle wheel problem) to current topics. The remaining chapters give an application motivated introduction to contemporary Stochastic Geometry, each one devoted to a particular branch of the subject: understanding spatial point patterns through intensity and conditional intensities; stochastic methods for image analysis; random fields and scale invariance; and the theory of Gibbs point processes. Exposing readers to a rich theory, this book will encourage further exploration of the subject and its wide applications.

This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.

Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and adding substantial new material, Statistical Analysis of Spatial and Spatio-Temporal Point Patter