advanced spatial statistics applications
Boolean Model
Category=PBM
Category=PBT
Category=PBWL
Compact Convex Sets
computational statistical analysis
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Geometric Ergodicity
geometric probability models
geometric sampling
Harris Recurrent
image data analysis
Kaplan Meier Estimator
Marked Point Process
Markov chain Monte Carlo
Markov chain Monte Carlo methods
Markov Point Processes
mathematical morphology
MCL
MCMC Method
Metropolis Chain
Morphological Image Analysis
Nash Inequalities
Pairwise Interaction Point Processes
Point Processes
Poisson Point Process
Poisson Process
Poisson Voronoi Tessellation
Random Closed Set
Random Compact Set
Random Set
random set theory
spatial point processes
Spectral Gap
statistical methods
Stochastic Geometry
stochastic geometry themes
Strauss Process
Unnormalized Density
Product details
- ISBN 9780849303968
- Weight: 730g
- Dimensions: 156 x 234mm
- Publication Date: 20 Oct 1998
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
Secure
checkout
Fast Shipping
Easy returns
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
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
