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Statistical Inference for Spatial Processes

1988 Mathematics
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Release : 1988
Genre : Mathematics
Kind : eBook
Book Rating : 202/5 ( reviews)

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Book Synopsis Statistical Inference for Spatial Processes by : B. D. Ripley

Download or read book Statistical Inference for Spatial Processes written by B. D. Ripley. This book was released on 1988. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistical Inference and Simulation for Spatial Point Processes

2003-09-25 Mathematics
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Release : 2003-09-25
Genre : Mathematics
Kind : eBook
Book Rating : 930/5 ( reviews)

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Book Synopsis Statistical Inference and Simulation for Spatial Point Processes by : Jesper Moller

Download or read book Statistical Inference and Simulation for Spatial Point Processes written by Jesper Moller. This book was released on 2003-09-25. Available in PDF, EPUB and Kindle. Book excerpt: 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 Poisson Processes

2012-12-06 Mathematics
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Release : 2012-12-06
Genre : Mathematics
Kind : eBook
Book Rating : 067/5 ( reviews)

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Book Synopsis Statistical Inference for Spatial Poisson Processes by : Yu A. Kutoyants

Download or read book Statistical Inference for Spatial Poisson Processes written by Yu A. Kutoyants. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistical inference for spatial processes

1991
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Release : 1991
Genre :
Kind : eBook
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Book Synopsis Statistical inference for spatial processes by : Brian D. Ripley

Download or read book Statistical inference for spatial processes written by Brian D. Ripley. This book was released on 1991. Available in PDF, EPUB and Kindle. Book excerpt:

Theory of Spatial Statistics

2019-03-19 Mathematics
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Release : 2019-03-19
Genre : Mathematics
Kind : eBook
Book Rating : 033/5 ( reviews)

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Book Synopsis Theory of Spatial Statistics by : M.N.M. van Lieshout

Download or read book Theory of Spatial Statistics written by M.N.M. van Lieshout. This book was released on 2019-03-19. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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