Stochastic geometry: likelihood and computation
by Barndorff-Nielsen, O. E., (Ole E.) Kendall, W. S. van Lieshout, M. N. M.
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 …
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- Full title :Stochastic geometry : likelihood and computation / edited by O.E. Barndorff-Nielsen, W.S. Kendall, M.N.M. van Lieshout.
Summary
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 themeso considerations of geometric sampling bias issueso tesselationso shapeo random setso image analysiso spectacular advances in likelihood-based inference now available to stochastic geometry through the techniques of Markov chain Monte Carlo
Read More ↓Edition Statements
- Publication Date:2019.
Publication Statements
- Publisher(s):Routledge
- Place of Publication:United States
- Language:eng
- Publication Date:2019.
The Physical Object
- Description:1 online resource (408 pages)
Edition Identifiers
- ISBN:9780203738276, 0203738276, 9781351413725, 1351413724, 9781351413718, 1351413716, 9781351413701, 1351413708
- DOI:10.1201/9780203738276
- oclc:on1105558609
- LC Classification:QA273.5
- Dewey Decimal:519.2/2
Table of Contents
PrefaceCrash Course in Stochastic GeometrySampling and CensoringLikelihood Inference for Spatial Point ProcessesMarkov Chain Monte Carlo and Spatial Point ProcessesTopics in Voronoi and Johnson-Mehl TessellationsMathematical MorphologyRandom Closed SetsGeneral Shape and Registration AnalysisNash InequalitiesIndex
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