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Statistical Inference and Simulation for Spatial Point Processes

Statistical Inference and Simulation for Spatial Point Processes
Author: Jesper Moller
Publisher: CRC Press
Total Pages: 320
Release: 2003-09-25
Genre: Mathematics
ISBN: 9780203496930

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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.


Statistical Inference for Spatial Processes

Statistical Inference for Spatial Processes
Author: B. D. Ripley
Publisher: Cambridge University Press
Total Pages: 162
Release: 1988
Genre: Mathematics
ISBN: 9780521424202

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The study of spatial processes and their applications is an important topic in statistics and finds wide application particularly in computer vision and image processing. This book is devoted to statistical inference in spatial statistics and is intended for specialists needing an introduction to the subject and to its applications. One of the themes of the book is the demonstration of how these techniques give new insights into classical procedures (including new examples in likelihood theory) and newer statistical paradigms such as Monte-Carlo inference and pseudo-likelihood. Professor Ripley also stresses the importance of edge effects and of lack of a unique asymptotic setting in spatial problems. Throughout, the author discusses the foundational issues posed and the difficulties, both computational and philosophical, which arise. The final chapters consider image restoration and segmentation methods and the averaging and summarising of images. Thus, the book will find wide appeal to researchers in computer vision, image processing, and those applying microscopy in biology, geology and materials science, as well as to statisticians interested in the foundations of their discipline.


Point Processes and Their Statistical Inference

Point Processes and Their Statistical Inference
Author: Alan Karr
Publisher: Routledge
Total Pages: 509
Release: 2017-09-06
Genre: Mathematics
ISBN: 1351423835

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Maintaining the excellent features that made the first edition so popular, this outstanding reference/text presents the only comprehensive treatment of the theory of point processes and statistical inference for point processes-highlighting both pointprocesses on the real line and sp;,.tial point processes. Thoroughly updated and revised to reflect changes since publication of the firstedition, the expanded Second EdiLion now contains a better organized and easierto-understand treatment of stationary point processes ... expanded treatment ofthe multiplicative intensity model ... expanded treatment of survival analysis . ..broadened consideration of applications ... an expanded and extended bibliographywith over 1,000 references ... and more than 3('() end-of-chapter exercises.


Spatial Point Patterns

Spatial Point Patterns
Author: Adrian Baddeley
Publisher: CRC Press
Total Pages: 830
Release: 2015-11-11
Genre: Mathematics
ISBN: 1482210215

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Modern Statistical Methodology and Software for Analyzing Spatial Point PatternsSpatial Point Patterns: Methodology and Applications with R shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on th


Spatial Point Process Modelling and Its Applications

Spatial Point Process Modelling and Its Applications
Author: Adrian Baddeley
Publisher: Publicacions de la Universitat Jaume I
Total Pages: 320
Release: 2004
Genre: Mathematics
ISBN: 9788480214759

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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.


Statistical Analysis of Spatial Point Patterns

Statistical Analysis of Spatial Point Patterns
Author: Peter Diggle
Publisher:
Total Pages: 166
Release: 1983
Genre: Mathematics
ISBN:

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Introduction; Preliminary testing for mapped patterns; Analysis of sparsely sampled patterns; Spatial point processes; Analysis of mapped patterns; Multivariate spatial point processes; Analysis of multivariate patterns.


Case Studies in Spatial Point Process Modeling

Case Studies in Spatial Point Process Modeling
Author: Adrian Baddeley
Publisher: Springer Science & Business Media
Total Pages: 312
Release: 2006-03-03
Genre: Mathematics
ISBN: 0387311440

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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


Theory of Spatial Statistics

Theory of Spatial Statistics
Author: M.N.M. van Lieshout
Publisher: CRC Press
Total Pages: 162
Release: 2019-03-19
Genre: Mathematics
ISBN: 0429627033

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Theory of Spatial Statistics: A Concise Introduction presents the most important models used in spatial statistics, including random fields and point processes, from a rigorous mathematical point of view and shows how to carry out statistical inference. It contains full proofs, real-life examples and theoretical exercises. Solutions to the latter are available in an appendix. Assuming maturity in probability and statistics, these concise lecture notes are self-contained and cover enough material for a semester course. They may also serve as a reference book for researchers. Features * Presents the mathematical foundations of spatial statistics. * Contains worked examples from mining, disease mapping, forestry, soil and environmental science, and criminology. * Gives pointers to the literature to facilitate further study. * Provides example code in R to encourage the student to experiment. * Offers exercises and their solutions to test and deepen understanding. The book is suitable for postgraduate and advanced undergraduate students in mathematics and statistics.


Handbook of Spatial Statistics

Handbook of Spatial Statistics
Author: Alan E. Gelfand
Publisher: CRC Press
Total Pages: 622
Release: 2010-03-19
Genre: Mathematics
ISBN: 1420072889

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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


Statistical Inference for Spatial Poisson Processes

Statistical Inference for Spatial Poisson Processes
Author: Yu A. Kutoyants
Publisher: Springer Science & Business Media
Total Pages: 282
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461217067

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This work is devoted to several problems of parametric (mainly) and nonparametric estimation through the observation of Poisson processes defined on general spaces. Poisson processes are quite popular in applied research and therefore they attract the attention of many statisticians. There are a lot of good books on point processes and many of them contain chapters devoted to statistical inference for general and partic ular models of processes. There are even chapters on statistical estimation problems for inhomogeneous Poisson processes in asymptotic statements. Nevertheless it seems that the asymptotic theory of estimation for nonlinear models of Poisson processes needs some development. Here nonlinear means the models of inhomogeneous Pois son processes with intensity function nonlinearly depending on unknown parameters. In such situations the estimators usually cannot be written in exact form and are given as solutions of some equations. However the models can be quite fruitful in en gineering problems and the existing computing algorithms are sufficiently powerful to calculate these estimators. Therefore the properties of estimators can be interesting too.