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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: a 'crash-course' introduction to key stochastic geometry themes; considerations of geometric sampling bias issues; tesselations; shape; random sets; image analysis; and spectacular advances in likelihood-based inference now available to stochastic geometry through the techniques of Markov chain Monte Carlo.
| ISBN | 0849303966 | | Pages | 408 | | ISBN13 | 9780849303968
(What's this?) | | Volumes | 1 | | Publisher | Taylor & Francis Inc | | Weight (grammes) | 730 | | Imprint | CRC Press Inc | | Published in | Bosa Roca | | Format | Hardback | | Series editor | Cox, D.R., Isham, V., et al | | Publication date | 20 Oct 1998 | | Series title | Chapman & Hall/CRC Monographs on Statistics & Applied Probability | | Non-book description | xv, 404 p. : | | Height (mm) | 235 | | Library of Congress | 98046543 | | Width (mm) | 156 | | DEWEY | 519.2 | | Spine width (mm) | 29 | | DEWEY edition | DC21 | | Academic level | Undergraduate, Postgraduate, Professional / Scholarly |
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| | | Contributors | | | | | | Preface | | | | 1 | | Crash course in stochastic geometry | | 1 | | 2 | | Sampling and censoring | | 37 | | 3 | | Likelihood inference for spatial point processes | | 79 | | 4 | | Markov chain Monte Carlo and spatial point processes | | 141 | | 5 | | Topics in Voronoi and Johnson-Mehl tessellations | | 173 | | 6 | | Mathematical morphology | | 199 | | 7 | | Random closed sets | | 285 | | 8 | | General shape and registration analysis | | 333 | | 9 | | Nash inequalities | | 365 | | | | Index | | 401 |
"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  Be the first to write a customer review
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