Stochastic Geometry: Likelihood and Computation

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Wilfrid S. Kendall, M.N.M. van Lieshout
CRC Press, Oct 20, 1998 - Mathematics - 408 pages
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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
 

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Contents

Prof A J Baddeley
33
Sampling and censoring
37
Likelihood inference for spatial point processes
79
Markov chain Monte Carlo and spatial point processes
141
Topics in Voronoi and JohnsonMehl tessellations
173
Mathematical morphology
199
Random closed sets
285
General shape and registration analysis
333
Nash inequalities
365
Index
401
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