Statistical Inference and Simulation for Spatial Point Processes
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€210.80
A01=Jesper Moller
A01=Rasmus Plenge Waagepetersen
advanced spatial statistics
Author_Jesper Moller
Author_Rasmus Plenge Waagepetersen
Bayesian spatial analysis
carlo
Category=PBT
chain
cox
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
homogeneous
inhomogeneous
likelihood inference methods
marked
markov
Markov chain Monte Carlo
monte
Monte Carlo algorithms for spatial data
perfect simulation methods
poisson
stochastic modeling techniques
strauss
Product details
- ISBN 9781584882657
- Weight: 640g
- Dimensions: 152 x 229mm
- Publication Date: 25 Sep 2003
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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Spatial point processes play a fundamental role in spatial statistics and today they are an active area of research with many new applications. Although other published works address different aspects of spatial point processes, most of the classical literature deals only with nonparametric methods, and a thorough treatment of the theory and applications of simulation-based inference is difficult to find. Written by researchers at the top of the field, this book collects and unifies recent theoretical advances and examples of applications. The authors examine Markov chain Monte Carlo algorithms and explore one of the most important recent developments in MCMC: perfect simulation procedures.
