Spatial Statistics and Modeling pp 111-148 | Cite as
Simulation of spatial models
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Abstract
Being able to simulate probability distributions and random variables is useful whenever we lack an analytic solution to a problem, be it combinatorial (number of ways to put 32 dominoes on an 8 × 8 grid), a search for maxima (Bayesian image reconstruction, cf. §2.2.2) or calculating integrals.
Keywords
Markov Chain Monte Carlo Markov Chain Spatial Model Gibbs Sampling Monte Carlo Markov Chain Method
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© Springer Science+Business Media, LLC 2010