Spatial Cluster Modelling
Regular price
€210.80
Absorption Line
advanced spatial cluster techniques
Bayesian spatial analysis
carlo
Category=PBT
chain
Cluster Centres
Cluster Distribution Function
Conditional Simulation
Cox Processes
disease mapping methods
distribution
distributions
ecological data clustering
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Full Conditional Distributions
Homogeneous Poisson Process
House Finch
Inhomogeneous Poisson Process
Log Gaussian Cox Process
Lung Cancer Mortality Risk
markov
MCMC
MCMC Simulation
monte
neuroimaging statistics
Neyman Scott Process
Pair Correlation Function
Partition Model
point
Point Process
point process inference
Poisson Point Process
Poisson Process
posterior
Posterior Distribution
Posterior Probability Intervals
prior
process
Skew Gaussian Distribution
Spatio Temporal Cluster
spatio-temporal modeling
Thomas Process
Van Lieshout
Product details
- ISBN 9781584882664
- Weight: 562g
- Dimensions: 156 x 234mm
- Publication Date: 16 May 2002
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
Secure
checkout
Fast Shipping
Easy returns
Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research.
In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal cluster modelling.
Many figures, some in full color, complement the text, and a single section of references cited makes it easy to locate source material. Leading specialists in the field of cluster modelling authored each chapter, and an introduction by the editors to each chapter provides a cohesion not typically found in contributed works. Spatial Cluster Modelling thus offers a singular opportunity to explore this exciting new field, understand its techniques, and apply them in your own research.
Lawson\, Andrew B.; Denison\, David G.T.
