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Statistical Inference and Simulation for Spatial Point Processes : Chapman & Hall/CRC Monographs on Statistics and Applied Probability - Jesper Moller

Statistical Inference and Simulation for Spatial Point Processes

By: Jesper Moller, Rasmus Plenge Waagepetersen

Hardcover | 25 September 2003 | Edition Number 1

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Technology now makes available huge amounts of spatial point process data, and new applications are continually arising in fields as diverse as astronomy, forestry, image analysis, and epidemiology. Although significant developments in both Markov Chain Monte Carlo (MCMC) techniques and spatial point processes have emerged in recent years, the literature has lacked a comprehensive, unified treatment of the theoretical advances - one that includes examples of real-world applications.
Statistical Inference and Simulation for Spatial Point Processes provides exactly that. With emphasis on MCMC methods, it fully explores simulation-based inference for spatial point processes. The treatment is detailed and authoritative, but at the same time self-contained and completely accessible. To simplify the mathematics, the authors restrict their attention to Euclidean space, but most of the results easily extend to more general state space. Five appendices provide all of the relevant background material, including a concise presentation of measure theory.
This is the first up-to-date, unified collection of theoretical advances and applications in this rapidly growing field. Readers learn not only the underlying principles and mathematics of simulation-based inference for spatial point processes, but through the book's many application examples they also get a clear, practical perspective on the implementation issues.
Industry Reviews

"This book is an extremely well-written summary of important topics in the analysis of spatial point processes. ... The authors do an excellent job focusing on those theoretical concepts and methods that are most important in applied research. Although other good books on spatial point processes are available, this is the first text to tackle difficult issues of simulation-based inference for such processes ... . [T]he text ... is remarkably easy to follow. ... The authors have a very impressive knack for explaining complicated topics very clearly ... . [This book] will no doubt prove an outstanding resource for researchers and students ... Its excellent survey of the vast array of models is reason enough to own it. As computer technology and speed advance ... the authors' clear, detailed, and comprehensive survey of simulation methods for spatial point processes will become increasingly important."
- Journal of the American Statistical Association

"... [T]his monograph is a well-written and concisely presented journey through the primary types of spatial point process frameworks. There is a useful equal balance between theoretical development and inference centred on simulation-based methods. ... This volume would be well suited for library purchase. ... [A] worthwhile investment."
- Journal of the Royal Statistics Society

"The book is very well organized and clearly written. It provides both an introduction and a review of the subject in a very condensed form. Thus it is an excellent support for a systematic approach to and an orientation for the current extensive literature with its different branches."
-Mathematical Reviews Issue 2004

"This book provides an excellent and up-to-date review of developments in this area. It covers most, if not all, of the major classes of models, and discusses methods for their approximate and exact simulation."
-ISI Short Book Reviews, Aug 04

"The book is a landmark in the development of point process statistics and sets standards in its field. It will be the key reference for all which is related to simulation in point process statistics."
- Dietrich Stoyan, Institut fuer Stochastik, Begakademie, Freiberg, Germany, in Statistics in Medicine, 2004

"Well and clearly written...self-contained...accessible to a wide audience."
-Zentralblatt MATH 1044

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