Stochastic geometry : likelihood and computation
著者
書誌事項
Stochastic geometry : likelihood and computation
（Monographs on statistics and applied probability, 80）
Chapman & Hall, c1999
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注記
"Papers given at the third Séminaire Européen de Statistique on 'Stochastic Geometry, Theory and Applications', held at Université Paul Sabatier, Toulouse, 13-18 May 1996" -- Pref
Includes bibliographical references and indexes
内容説明・目次
内容説明
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
目次
Preface. Recent Developments in Stochastic Geometry and Stereology. Markov Chain Monte Carlo Techniques. Markov Chain Monte Carlo and Spatial Point Process. Topics in Voronoi and Johnson-Mehl Tessellations. Mathematical Morphology. Rates of Convergence of Markov Chains. Shape Theory. Random Sets: Results, Problems and Perspectives.
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