1st Edition

Stochastic Geometry
Likelihood and Computation




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ISBN 9780849303968
Published October 20, 1998 by Chapman and Hall/CRC
408 Pages

USD $180.00

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Book Description

Stochastic geometry involves the study of random geometric structures, and blends geometric, probabilistic, and statistical methods to provide powerful techniques for modeling and analysis. Recent developments in computational statistical analysis, particularly Markov chain Monte Carlo, have enormously extended the range of feasible applications. Stochastic Geometry: Likelihood and Computation provides a coordinated collection of chapters on important aspects of the rapidly developing field of stochastic geometry, including:
o a "crash-course" introduction to key stochastic geometry themes
o considerations of geometric sampling bias issues
o tesselations
o shape
o random sets
o image analysis
o spectacular advances in likelihood-based inference now available to stochastic geometry through the techniques of Markov chain Monte Carlo

Table of Contents

Preface
Crash Course in Stochastic Geometry
Sampling and Censoring
Likelihood Inference for Spatial Point Processes
Markov Chain Monte Carlo and Spatial Point Processes
Topics in Voronoi and Johnson-Mehl Tessellations
Mathematical Morphology
Random Closed Sets
General Shape and Registration Analysis
Nash Inequalities
Index

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Editor(s)

Biography

O.E. Barndorff-Nielsen Professor of Theoretical Statistics Institute of Mathematics Aarhus Denmark. W.S. Kendall Professor of Statistics University of Warwick UK and M.N.M. van Lieshout Centre for Science and Information (CWI) Amsterdam The Netherlands

Reviews

"This useful collection of papers highlights various aspects of modern stochastic geometry. The papers included here provide a rare opportunity to grasp new major trends in stochastic geometry and related areas."
-Mathematical Reviews